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algorithm</title> <meta name="description" content="Search results for: Genetic algorithm"> <meta name="keywords" content="Genetic algorithm"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none 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action="https://publications.waset.org/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="Genetic algorithm"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 3635</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: Genetic algorithm</h1> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3635</span> Application of Adaptive Genetic Algorithm in Function Optimization</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Panpan%20Xu">Panpan Xu</a>, <a href="https://publications.waset.org/search?q=Shulin%20Sui"> Shulin Sui</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>The crossover probability and mutation probability are the two important factors in genetic algorithm. The adaptive genetic algorithm can improve the convergence performance of genetic algorithm, in which the crossover probability and mutation probability are adaptively designed with the changes of fitness value. We apply adaptive genetic algorithm into a function optimization problem. The numerical experiment represents that adaptive genetic algorithm improves the convergence speed and avoids local convergence.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Genetic%20algorithm" title="Genetic algorithm">Genetic algorithm</a>, <a href="https://publications.waset.org/search?q=Adaptive%20genetic%20algorithm" title=" Adaptive genetic algorithm"> Adaptive genetic algorithm</a>, <a href="https://publications.waset.org/search?q=Function%20optimization." title=" Function optimization."> Function optimization.</a> </p> <a href="https://publications.waset.org/10003327/application-of-adaptive-genetic-algorithm-in-function-optimization" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10003327/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10003327/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10003327/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10003327/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10003327/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10003327/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10003327/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10003327/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10003327/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10003327/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10003327.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1724</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3634</span> Genetic Mining: Using Genetic Algorithm for Topic based on Concept Distribution</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=S.%20M.%20Khalessizadeh">S. M. Khalessizadeh</a>, <a href="https://publications.waset.org/search?q=R.%20Zaefarian"> R. Zaefarian</a>, <a href="https://publications.waset.org/search?q=S.H.%20Nasseri"> S.H. Nasseri</a>, <a href="https://publications.waset.org/search?q=E.%20Ardil"> E. Ardil</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Today, Genetic Algorithm has been used to solve wide range of optimization problems. Some researches conduct on applying Genetic Algorithm to text classification, summarization and information retrieval system in text mining process. This researches show a better performance due to the nature of Genetic Algorithm. In this paper a new algorithm for using Genetic Algorithm in concept weighting and topic identification, based on concept standard deviation will be explored. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Genetic%20Algorithm" title="Genetic Algorithm">Genetic Algorithm</a>, <a href="https://publications.waset.org/search?q=Text%20Mining" title=" Text Mining"> Text Mining</a>, <a href="https://publications.waset.org/search?q=Term%20Weighting" title=" Term Weighting"> Term Weighting</a>, <a href="https://publications.waset.org/search?q=Concept%20Extraction" title="Concept Extraction">Concept Extraction</a>, <a href="https://publications.waset.org/search?q=Concept%20Distribution." title=" Concept Distribution."> Concept Distribution.</a> </p> <a href="https://publications.waset.org/10232/genetic-mining-using-genetic-algorithm-for-topic-based-on-concept-distribution" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10232/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10232/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10232/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10232/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10232/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10232/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10232/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10232/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10232/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10232/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10232.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">3715</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3633</span> Analog Circuit Design using Genetic Algorithm: Modified</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Amod%20P.%20Vaze">Amod P. Vaze</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Genetic Algorithm has been used to solve wide range of optimization problems. Some researches conduct on applying Genetic Algorithm to analog circuit design automation. These researches show a better performance due to the nature of Genetic Algorithm. In this paper a modified Genetic Algorithm is applied for analog circuit design automation. The modifications are made to the topology of the circuit. These modifications will lead to a more computationally efficient algorithm.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Genetic%20algorithm" title="Genetic algorithm">Genetic algorithm</a>, <a href="https://publications.waset.org/search?q=analog%20circuits" title=" analog circuits"> analog circuits</a>, <a href="https://publications.waset.org/search?q=design." title=" design."> design.</a> </p> <a href="https://publications.waset.org/14807/analog-circuit-design-using-genetic-algorithm-modified" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/14807/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/14807/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/14807/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/14807/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/14807/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/14807/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/14807/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/14807/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/14807/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/14807/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/14807.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">2293</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3632</span> Application of Hybrid Genetic Algorithm Based on Simulated Annealing in Function Optimization</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Panpan%20Xu">Panpan Xu</a>, <a href="https://publications.waset.org/search?q=Shulin%20Sui"> Shulin Sui</a>, <a href="https://publications.waset.org/search?q=Zongjie%20Du"> Zongjie Du</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Genetic algorithm is widely used in optimization problems for its excellent global search capabilities and highly parallel processing capabilities; but, it converges prematurely and has a poor local optimization capability in actual operation. Simulated annealing algorithm can avoid the search process falling into local optimum. A hybrid genetic algorithm based on simulated annealing is designed by combining the advantages of genetic algorithm and simulated annealing algorithm. The numerical experiment represents the hybrid genetic algorithm can be applied to solve the function optimization problems efficiently. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Genetic%20algorithm" title="Genetic algorithm">Genetic algorithm</a>, <a href="https://publications.waset.org/search?q=Simulated%20annealing" title=" Simulated annealing"> Simulated annealing</a>, <a href="https://publications.waset.org/search?q=Hybrid%0D%0Agenetic%20algorithm" title=" Hybrid genetic algorithm"> Hybrid genetic algorithm</a>, <a href="https://publications.waset.org/search?q=Function%20optimization." title=" Function optimization."> Function optimization.</a> </p> <a href="https://publications.waset.org/10003238/application-of-hybrid-genetic-algorithm-based-on-simulated-annealing-in-function-optimization" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10003238/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10003238/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10003238/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10003238/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10003238/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10003238/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10003238/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10003238/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10003238/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10003238/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10003238.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">2550</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3631</span> Solving the Quadratic Assignment Problems by a Genetic Algorithm with a New Replacement Strategy</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Yongzhong%20Wu">Yongzhong Wu</a>, <a href="https://publications.waset.org/search?q=Ping%20Ji"> Ping Ji</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper proposes a genetic algorithm based on a new replacement strategy to solve the quadratic assignment problems, which are NP-hard. The new replacement strategy aims to improve the performance of the genetic algorithm through well balancing the convergence of the searching process and the diversity of the population. In order to test the performance of the algorithm, the instances in QAPLIB, a quadratic assignment problem library, are tried and the results are compared with those reported in the literature. The performance of the genetic algorithm is promising. The significance is that this genetic algorithm is generic. It does not rely on problem-specific genetic operators, and may be easily applied to various types of combinatorial problems. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Quadratic%20assignment%20problem" title="Quadratic assignment problem">Quadratic assignment problem</a>, <a href="https://publications.waset.org/search?q=Genetic%20algorithm" title=" Genetic algorithm"> Genetic algorithm</a>, <a href="https://publications.waset.org/search?q=Replacement%20strategy" title=" Replacement strategy"> Replacement strategy</a>, <a href="https://publications.waset.org/search?q=QAPLIB." title=" QAPLIB."> QAPLIB.</a> </p> <a href="https://publications.waset.org/8342/solving-the-quadratic-assignment-problems-by-a-genetic-algorithm-with-a-new-replacement-strategy" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/8342/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/8342/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/8342/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/8342/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/8342/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/8342/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/8342/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/8342/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/8342/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/8342/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/8342.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">2748</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3630</span> A New Algorithm to Stereo Correspondence Using Rank Transform and Morphology Based On Genetic Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Razagh%20Hafezi">Razagh Hafezi</a>, <a href="https://publications.waset.org/search?q=Ahmad%20Keshavarz"> Ahmad Keshavarz</a>, <a href="https://publications.waset.org/search?q=Vida%20Moshfegh"> Vida Moshfegh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a novel algorithm of stereo correspondence with rank transform. In this algorithm we used the genetic algorithm to achieve the accurate disparity map. Genetic algorithms are efficient search methods based on principles of population genetic, i.e. mating, chromosome crossover, gene mutation, and natural selection. Finally morphology is employed to remove the errors and discontinuities. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=genetic%20algorithm" title="genetic algorithm">genetic algorithm</a>, <a href="https://publications.waset.org/search?q=morphology" title=" morphology"> morphology</a>, <a href="https://publications.waset.org/search?q=rank%20transform" title=" rank transform"> rank transform</a>, <a href="https://publications.waset.org/search?q=stereo%20correspondence" title=" stereo correspondence"> stereo correspondence</a> </p> <a href="https://publications.waset.org/2671/a-new-algorithm-to-stereo-correspondence-using-rank-transform-and-morphology-based-on-genetic-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/2671/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/2671/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/2671/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/2671/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/2671/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/2671/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/2671/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/2671/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/2671/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/2671/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/2671.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">2173</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3629</span> An Innovative Fuzzy Decision Making Based Genetic Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=M.%20A.%20Sharbafi">M. A. Sharbafi</a>, <a href="https://publications.waset.org/search?q=M.%20Shakiba%20Herfeh"> M. Shakiba Herfeh</a>, <a href="https://publications.waset.org/search?q=Caro%20Lucas"> Caro Lucas</a>, <a href="https://publications.waset.org/search?q=A.%20Mohammadi%20Nejad"> A. Mohammadi Nejad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Several researchers have proposed methods about combination of Genetic Algorithm (GA) and Fuzzy Logic (the use of GA to obtain fuzzy rules and application of fuzzy logic in optimization of GA). In this paper, we suggest a new method in which fuzzy decision making is used to improve the performance of genetic algorithm. In the suggested method, we determine the alleles that enhance the fitness of chromosomes and try to insert them to the next generation. In this algorithm we try to present an innovative vaccination in the process of reproduction in genetic algorithm, with considering the trade off between exploration and exploitation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Genetic%20Algorithm" title="Genetic Algorithm">Genetic Algorithm</a>, <a href="https://publications.waset.org/search?q=Fuzzy%20Decision%20Making." title=" Fuzzy Decision Making."> Fuzzy Decision Making.</a> </p> <a href="https://publications.waset.org/14568/an-innovative-fuzzy-decision-making-based-genetic-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/14568/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/14568/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/14568/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/14568/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/14568/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/14568/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/14568/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/14568/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/14568/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/14568/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/14568.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1608</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3628</span> Restartings: A Technique to Improve Classic Genetic Algorithms Performance </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Grigorios%20N.%20Beligiannis">Grigorios N. Beligiannis</a>, <a href="https://publications.waset.org/search?q=Georgios%20A.%20Tsirogiannis"> Georgios A. Tsirogiannis</a>, <a href="https://publications.waset.org/search?q=Panayotis%20E.%20Pintelas"> Panayotis E. Pintelas</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>In this contribution, a way to enhance the performance of the classic Genetic Algorithm is proposed. The idea of restarting a Genetic Algorithm is applied in order to obtain better knowledge of the solution space of the problem. A new operator of 'insertion' is introduced so as to exploit (utilize) the information that has already been collected before the restarting procedure. Finally, numerical experiments comparing the performance of the classic Genetic Algorithm and the Genetic Algorithm with restartings, for some well known test functions, are given.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Genetic%20Algorithms" title="Genetic Algorithms">Genetic Algorithms</a>, <a href="https://publications.waset.org/search?q=Restartings" title=" Restartings"> Restartings</a>, <a href="https://publications.waset.org/search?q=Search%20space%20exploration" title=" Search space exploration"> Search space exploration</a>, <a href="https://publications.waset.org/search?q=Search%20space%20exploitation." title=" Search space exploitation."> Search space exploitation.</a> </p> <a href="https://publications.waset.org/12222/restartings-a-technique-to-improve-classic-genetic-algorithms-performance" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/12222/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/12222/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/12222/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/12222/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/12222/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/12222/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/12222/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/12222/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/12222/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/12222/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/12222.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">2138</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3627</span> Fast and Accurate Reservoir Modeling: Genetic Algorithm versus DIRECT Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Mohsen%20Ebrahimi">Mohsen Ebrahimi</a>, <a href="https://publications.waset.org/search?q=Milad%20M.%20Rabieh"> Milad M. Rabieh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, two very different optimization algorithms, Genetic and DIRECT algorithms, are used to history match a bottomhole pressure response for a reservoir with wellbore storage and skin with the best possible analytical model. No initial guesses are available for reservoir parameters. The results show that the matching process is much faster and more accurate for DIRECT method in comparison with Genetic algorithm. It is furthermore concluded that the DIRECT algorithm does not need any initial guesses, whereas Genetic algorithm needs to be tuned according to initial guesses. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=DIRECT%20algorithm" title="DIRECT algorithm">DIRECT algorithm</a>, <a href="https://publications.waset.org/search?q=Genetic%20algorithm" title=" Genetic algorithm"> Genetic algorithm</a>, <a href="https://publications.waset.org/search?q=Analytical%0Amodeling" title=" Analytical modeling"> Analytical modeling</a>, <a href="https://publications.waset.org/search?q=History%20match" title=" History match"> History match</a> </p> <a href="https://publications.waset.org/2594/fast-and-accurate-reservoir-modeling-genetic-algorithm-versus-direct-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/2594/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/2594/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/2594/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/2594/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/2594/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/2594/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/2594/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/2594/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/2594/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/2594/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/2594.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1756</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3626</span> Initializing K-Means using Genetic Algorithms</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Bashar%20Al-Shboul">Bashar Al-Shboul</a>, <a href="https://publications.waset.org/search?q=Sung-Hyon%20Myaeng"> Sung-Hyon Myaeng</a> </p> <p class="card-text"><strong>Abstract:</strong></p> K-Means (KM) is considered one of the major algorithms widely used in clustering. However, it still has some problems, and one of them is in its initialization step where it is normally done randomly. Another problem for KM is that it converges to local minima. Genetic algorithms are one of the evolutionary algorithms inspired from nature and utilized in the field of clustering. In this paper, we propose two algorithms to solve the initialization problem, Genetic Algorithm Initializes KM (GAIK) and KM Initializes Genetic Algorithm (KIGA). To show the effectiveness and efficiency of our algorithms, a comparative study was done among GAIK, KIGA, Genetic-based Clustering Algorithm (GCA), and FCM [19]. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Clustering" title="Clustering">Clustering</a>, <a href="https://publications.waset.org/search?q=Genetic%20Algorithms" title=" Genetic Algorithms"> Genetic Algorithms</a>, <a href="https://publications.waset.org/search?q=K-means." title=" K-means."> K-means.</a> </p> <a href="https://publications.waset.org/12873/initializing-k-means-using-genetic-algorithms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/12873/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/12873/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/12873/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/12873/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/12873/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/12873/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/12873/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/12873/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/12873/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/12873/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/12873.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">2102</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3625</span> Multi Objective Micro Genetic Algorithm for Combine and Reroute Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Soottipoom%20Yaowiwat">Soottipoom Yaowiwat</a>, <a href="https://publications.waset.org/search?q=Manoj%20Lohatepanont"> Manoj Lohatepanont</a>, <a href="https://publications.waset.org/search?q=Proadpran%20Punyabukkana"> Proadpran Punyabukkana</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Several approaches such as linear programming, network modeling, greedy heuristic and decision support system are well-known approaches in solving irregular airline operation problem. This paper presents an alternative approach based on Multi Objective Micro Genetic Algorithm. The aim of this research is to introduce the concept of Multi Objective Micro Genetic Algorithm as a tool to solve irregular airline operation, combine and reroute problem. The experiment result indicated that the model could obtain optimal solutions within a few second. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Irregular%20Airline%20Operation" title="Irregular Airline Operation">Irregular Airline Operation</a>, <a href="https://publications.waset.org/search?q=Combine%20and%20RerouteRoutine" title=" Combine and RerouteRoutine"> Combine and RerouteRoutine</a>, <a href="https://publications.waset.org/search?q=Genetic%20Algorithm" title=" Genetic Algorithm"> Genetic Algorithm</a>, <a href="https://publications.waset.org/search?q=Micro%20Genetic%20Algorithm" title=" Micro Genetic Algorithm"> Micro Genetic Algorithm</a>, <a href="https://publications.waset.org/search?q=Multi%20ObjectiveOptimization" title=" Multi ObjectiveOptimization"> Multi ObjectiveOptimization</a>, <a href="https://publications.waset.org/search?q=Evolutionary%20Algorithm." title=" Evolutionary Algorithm."> Evolutionary Algorithm.</a> </p> <a href="https://publications.waset.org/1335/multi-objective-micro-genetic-algorithm-for-combine-and-reroute-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/1335/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/1335/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/1335/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/1335/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/1335/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/1335/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/1335/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/1335/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/1335/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/1335/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/1335.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1643</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3624</span> A New Heuristic for Improving the Performance of Genetic Algorithm </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Warattapop%20Chainate">Warattapop Chainate</a>, <a href="https://publications.waset.org/search?q=Peeraya%20Thapatsuwan"> Peeraya Thapatsuwan</a>, <a href="https://publications.waset.org/search?q=Pupong%20Pongcharoen">Pupong Pongcharoen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The hybridisation of genetic algorithm with heuristics has been shown to be one of an effective way to improve its performance. In this work, genetic algorithm hybridised with four heuristics including a new heuristic called neighbourhood improvement were investigated through the classical travelling salesman problem. The experimental results showed that the proposed heuristic outperformed other heuristics both in terms of quality of the results obtained and the computational time. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Genetic%20Algorithm" title="Genetic Algorithm">Genetic Algorithm</a>, <a href="https://publications.waset.org/search?q=Hybridisation" title=" Hybridisation"> Hybridisation</a>, <a href="https://publications.waset.org/search?q=Metaheuristics" title=" Metaheuristics"> Metaheuristics</a>, <a href="https://publications.waset.org/search?q=Travelling%20Salesman%20Problem." title="Travelling Salesman Problem.">Travelling Salesman Problem.</a> </p> <a href="https://publications.waset.org/14842/a-new-heuristic-for-improving-the-performance-of-genetic-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/14842/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/14842/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/14842/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/14842/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/14842/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/14842/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/14842/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/14842/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/14842/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/14842/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/14842.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1849</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3623</span> Statistical Genetic Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Mohammad%20Ali%20Tabarzad">Mohammad Ali Tabarzad</a>, <a href="https://publications.waset.org/search?q=Caro%20Lucas"> Caro Lucas</a>, <a href="https://publications.waset.org/search?q=Ali%20Hamzeh"> Ali Hamzeh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Adaptive Genetic Algorithms extend the Standard Gas to use dynamic procedures to apply evolutionary operators such as crossover, mutation and selection. In this paper, we try to propose a new adaptive genetic algorithm, which is based on the statistical information of the population as a guideline to tune its crossover, selection and mutation operators. This algorithms is called Statistical Genetic Algorithm and is compared with traditional GA in some benchmark problems. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Genetic%20Algorithms" title="Genetic Algorithms">Genetic Algorithms</a>, <a href="https://publications.waset.org/search?q=Statistical%20Information%20ofthe%20Population" title=" Statistical Information ofthe Population"> Statistical Information ofthe Population</a>, <a href="https://publications.waset.org/search?q=PAUX" title=" PAUX"> PAUX</a>, <a href="https://publications.waset.org/search?q=SSO." title=" SSO."> SSO.</a> </p> <a href="https://publications.waset.org/3717/statistical-genetic-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/3717/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/3717/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/3717/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/3717/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/3717/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/3717/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/3717/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/3717/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/3717/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/3717/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/3717.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1754</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3622</span> Development of Heterogeneous Parallel Genetic Simulated Annealing Using Multi-Niche Crowding</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Z.%20G.%20Wang">Z. G. Wang</a>, <a href="https://publications.waset.org/search?q=M.%20Rahman"> M. Rahman</a>, <a href="https://publications.waset.org/search?q=Y.%20S.%20Wong"> Y. S. Wong</a>, <a href="https://publications.waset.org/search?q=K.%20S.%20Neo"> K. S. Neo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a new hybrid of genetic algorithm (GA) and simulated annealing (SA), referred to as GSA, is presented. In this algorithm, SA is incorporated into GA to escape from local optima. The concept of hierarchical parallel GA is employed to parallelize GSA for the optimization of multimodal functions. In addition, multi-niche crowding is used to maintain the diversity in the population of the parallel GSA (PGSA). The performance of the proposed algorithms is evaluated against a standard set of multimodal benchmark functions. The multi-niche crowding PGSA and normal PGSA show some remarkable improvement in comparison with the conventional parallel genetic algorithm and the breeder genetic algorithm (BGA). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Crowding" title="Crowding">Crowding</a>, <a href="https://publications.waset.org/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/search?q=parallel%20geneticalgorithm" title=" parallel geneticalgorithm"> parallel geneticalgorithm</a>, <a href="https://publications.waset.org/search?q=simulated%20annealing." title=" simulated annealing."> simulated annealing.</a> </p> <a href="https://publications.waset.org/5118/development-of-heterogeneous-parallel-genetic-simulated-annealing-using-multi-niche-crowding" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/5118/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/5118/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/5118/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/5118/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/5118/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/5118/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/5118/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/5118/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/5118/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/5118/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/5118.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1587</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3621</span> Optimization of Supersonic Ejector via Sequence-Adapted Micro-Genetic Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Kolar%20Jan">Kolar Jan</a>, <a href="https://publications.waset.org/search?q=Dvorak%20Vaclav"> Dvorak Vaclav</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>In this study, an optimization of supersonic air-to-air ejector is carried out by a recently developed single-objective genetic algorithm based on adaption of sequence of individuals. Adaptation of sequence is based on Shape-based distance of individuals and embedded micro-genetic algorithm. The optimal sequence found defines the succession of CFD-aimed objective calculation within each generation of regular micro-genetic algorithm. A spring-based deformation mutates the computational grid starting the initial individualvia adapted population in the optimized sequence. Selection of a generation initial individual is knowledge-based. A direct comparison of the newly defined and standard micro-genetic algorithm is carried out for supersonic air-to-air ejector. The only objective is to minimize the loose of total stagnation pressure in the ejector. The result is that sequence-adopted micro-genetic algorithm can provide comparative results to standard algorithm but in significantly lower number of overall CFD iteration steps.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Grid%20deformation" title="Grid deformation">Grid deformation</a>, <a href="https://publications.waset.org/search?q=Micro-genetic%20algorithm" title=" Micro-genetic algorithm"> Micro-genetic algorithm</a>, <a href="https://publications.waset.org/search?q=shapebased%0D%0Asequence" title=" shapebased sequence"> shapebased sequence</a>, <a href="https://publications.waset.org/search?q=supersonic%20ejector." title=" supersonic ejector."> supersonic ejector.</a> </p> <a href="https://publications.waset.org/4441/optimization-of-supersonic-ejector-via-sequence-adapted-micro-genetic-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/4441/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/4441/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/4441/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/4441/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/4441/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/4441/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/4441/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/4441/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/4441/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/4441/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/4441.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1564</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3620</span> Simulation of Robotic Arm using Genetic Algorithm and AHP </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=V.%20K.%20Banga">V. K. Banga</a>, <a href="https://publications.waset.org/search?q=Y.%20Singh"> Y. Singh</a>, <a href="https://publications.waset.org/search?q=R.%20Kumar"> R. Kumar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we have proposed a low cost optimized solution for the movement of a three-arm manipulator using Genetic Algorithm (GA) and Analytical Hierarchy Process (AHP). A scheme is given for optimizing the movement of robotic arm with the help of Genetic Algorithm so that the minimum energy consumption criteria can be achieved. As compared to Direct Kinematics, Inverse Kinematics evolved two solutions out of which the best-fit solution is selected with the help of Genetic Algorithm and is kept in search space for future use. The Inverse Kinematics, Fitness Value evaluation and Binary Encoding like tasks are simulated and tested. Although, three factors viz. Movement, Friction and Least Settling Time (or Min. Vibration) are used for finding the Fitness Function / Fitness Values, however some more factors can also be considered. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Inverse%20Kinematics" title="Inverse Kinematics">Inverse Kinematics</a>, <a href="https://publications.waset.org/search?q=Genetic%20Algorithm%20%28GA%29" title=" Genetic Algorithm (GA)"> Genetic Algorithm (GA)</a>, <a href="https://publications.waset.org/search?q=Analytical%20Hierarchy%20Process%20%28AHP%29" title="Analytical Hierarchy Process (AHP)">Analytical Hierarchy Process (AHP)</a>, <a href="https://publications.waset.org/search?q=Fitness%20Value" title=" Fitness Value"> Fitness Value</a>, <a href="https://publications.waset.org/search?q=Fitness%20Function." title=" Fitness Function."> Fitness Function.</a> </p> <a href="https://publications.waset.org/5038/simulation-of-robotic-arm-using-genetic-algorithm-and-ahp" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/5038/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/5038/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/5038/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/5038/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/5038/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/5038/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/5038/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/5038/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/5038/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/5038/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/5038.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">2964</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3619</span> A Genetic and Simulated Annealing Based Algorithms for Solving the Flow Assignment Problem in Computer Networks </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Tarek%20M.%20Mahmoud">Tarek M. Mahmoud </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Selecting the routes and the assignment of link flow in a computer communication networks are extremely complex combinatorial optimization problems. Metaheuristics, such as genetic or simulated annealing algorithms, are widely applicable heuristic optimization strategies that have shown encouraging results for a large number of difficult combinatorial optimization problems. This paper considers the route selection and hence the flow assignment problem. A genetic algorithm and simulated annealing algorithm are used to solve this problem. A new hybrid algorithm combining the genetic with the simulated annealing algorithm is introduced. A modification of the genetic algorithm is also introduced. Computational experiments with sample networks are reported. The results show that the proposed modified genetic algorithm is efficient in finding good solutions of the flow assignment problem compared with other techniques. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Genetic%20Algorithms" title="Genetic Algorithms">Genetic Algorithms</a>, <a href="https://publications.waset.org/search?q=Flow%20Assignment" title=" Flow Assignment"> Flow Assignment</a>, <a href="https://publications.waset.org/search?q=Routing" title=" Routing"> Routing</a>, <a href="https://publications.waset.org/search?q=Computer%20network" title="Computer network">Computer network</a>, <a href="https://publications.waset.org/search?q=Simulated%20Annealing." title=" Simulated Annealing."> Simulated Annealing.</a> </p> <a href="https://publications.waset.org/11820/a-genetic-and-simulated-annealing-based-algorithms-for-solving-the-flow-assignment-problem-in-computer-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/11820/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/11820/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/11820/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/11820/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/11820/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/11820/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/11820/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/11820/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/11820/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/11820/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/11820.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">2256</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3618</span> A Genetic Algorithm for Clustering on Image Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Qin%20Ding">Qin Ding</a>, <a href="https://publications.waset.org/search?q=Jim%20Gasvoda"> Jim Gasvoda</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Clustering is the process of subdividing an input data set into a desired number of subgroups so that members of the same subgroup are similar and members of different subgroups have diverse properties. Many heuristic algorithms have been applied to the clustering problem, which is known to be NP Hard. Genetic algorithms have been used in a wide variety of fields to perform clustering, however, the technique normally has a long running time in terms of input set size. This paper proposes an efficient genetic algorithm for clustering on very large data sets, especially on image data sets. The genetic algorithm uses the most time efficient techniques along with preprocessing of the input data set. We test our algorithm on both artificial and real image data sets, both of which are of large size. The experimental results show that our algorithm outperforms the k-means algorithm in terms of running time as well as the quality of the clustering.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Clustering" title="Clustering">Clustering</a>, <a href="https://publications.waset.org/search?q=data%20mining" title=" data mining"> data mining</a>, <a href="https://publications.waset.org/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/search?q=image%20data." title=" image data."> image data.</a> </p> <a href="https://publications.waset.org/13536/a-genetic-algorithm-for-clustering-on-image-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/13536/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/13536/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/13536/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/13536/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/13536/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/13536/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/13536/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/13536/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/13536/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/13536/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/13536.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">2053</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3617</span> An Optimization Algorithm Based on Dynamic Schema with Dissimilarities and Similarities of Chromosomes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Radhwan%20Yousif%20Sedik%20Al-Jawadi">Radhwan Yousif Sedik Al-Jawadi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Optimization is necessary for finding appropriate solutions to a range of real-life problems. In particular, genetic (or more generally, evolutionary) algorithms have proved very useful in solving many problems for which analytical solutions are not available. In this paper, we present an optimization algorithm called Dynamic Schema with Dissimilarity and Similarity of Chromosomes (DSDSC) which is a variant of the classical genetic algorithm. This approach constructs new chromosomes from a schema and pairs of existing ones by exploring their dissimilarities and similarities. To show the effectiveness of the algorithm, it is tested and compared with the classical GA, on 15 two-dimensional optimization problems taken from literature. We have found that, in most cases, our method is better than the classical genetic algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Genetic%20algorithm" title="Genetic algorithm">Genetic algorithm</a>, <a href="https://publications.waset.org/search?q=similarity%20and%20dissimilarity" title=" similarity and dissimilarity"> similarity and dissimilarity</a>, <a href="https://publications.waset.org/search?q=chromosome%20injection" title=" chromosome injection"> chromosome injection</a>, <a href="https://publications.waset.org/search?q=dynamic%20schema." title=" dynamic schema."> dynamic schema.</a> </p> <a href="https://publications.waset.org/10005170/an-optimization-algorithm-based-on-dynamic-schema-with-dissimilarities-and-similarities-of-chromosomes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10005170/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10005170/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10005170/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10005170/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10005170/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10005170/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10005170/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10005170/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10005170/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10005170/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10005170.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1297</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3616</span> Robotic Arm Control with Neural Networks Using Genetic Algorithm Optimization Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=A.%20Pajaziti">A. Pajaziti</a>, <a href="https://publications.waset.org/search?q=H.%20Cana"> H. Cana</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>In this paper, the structural genetic algorithm is used to optimize the neural network to control the joint movements of robotic arm. The robotic arm has also been modeled in 3D and simulated in real-time in MATLAB. It is found that Neural Networks provide a simple and effective way to control the robot tasks. Computer simulation examples are given to illustrate the significance of this method. By combining Genetic Algorithm optimization method and Neural Networks for the given robotic arm with 5 D.O.F. the obtained the results shown that the base joint movements overshooting time without controller was about 0.5 seconds, while with Neural Network controller (optimized with Genetic Algorithm) was about 0.2 seconds, and the population size of 150 gave best results.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Robotic%20Arm" title="Robotic Arm">Robotic Arm</a>, <a href="https://publications.waset.org/search?q=Neural%20Network" title=" Neural Network"> Neural Network</a>, <a href="https://publications.waset.org/search?q=Genetic%20Algorithm" title=" Genetic Algorithm"> Genetic Algorithm</a>, <a href="https://publications.waset.org/search?q=Optimization." title=" Optimization."> Optimization.</a> </p> <a href="https://publications.waset.org/9999081/robotic-arm-control-with-neural-networks-using-genetic-algorithm-optimization-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/9999081/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/9999081/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/9999081/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/9999081/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/9999081/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/9999081/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/9999081/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/9999081/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/9999081/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/9999081/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/9999081.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">3595</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3615</span> An Effective Hybrid Genetic Algorithm for Job Shop Scheduling Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Bin%20Cai">Bin Cai</a>, <a href="https://publications.waset.org/search?q=Shilong%20Wang"> Shilong Wang</a>, <a href="https://publications.waset.org/search?q=Haibo%20Hu"> Haibo Hu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>The job shop scheduling problem (JSSP) is well known as one of the most difficult combinatorial optimization problems. This paper presents a hybrid genetic algorithm for the JSSP with the objective of minimizing makespan. The efficiency of the genetic algorithm is enhanced by integrating it with a local search method. The chromosome representation of the problem is based on operations. Schedules are constructed using a procedure that generates full active schedules. In each generation, a local search heuristic based on Nowicki and Smutnicki-s neighborhood is applied to improve the solutions. The approach is tested on a set of standard instances taken from the literature and compared with other approaches. The computation results validate the effectiveness of the proposed algorithm.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Genetic%20algorithm" title="Genetic algorithm">Genetic algorithm</a>, <a href="https://publications.waset.org/search?q=Job%20shop%20scheduling%20problem" title=" Job shop scheduling problem"> Job shop scheduling problem</a>, <a href="https://publications.waset.org/search?q=Local%20search" title=" Local search"> Local search</a>, <a href="https://publications.waset.org/search?q=Meta-heuristic%20algorithm" title=" Meta-heuristic algorithm"> Meta-heuristic algorithm</a> </p> <a href="https://publications.waset.org/7321/an-effective-hybrid-genetic-algorithm-for-job-shop-scheduling-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/7321/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/7321/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/7321/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/7321/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/7321/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/7321/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/7321/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/7321/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/7321/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/7321/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/7321.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1653</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3614</span> A Genetic Algorithm to Schedule the Flow Shop Problem under Preventive Maintenance Activities</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=J.%20Kaabi"> J. Kaabi</a>, <a href="https://publications.waset.org/search?q=Y.%20Harrath"> Y. Harrath</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>This paper studied the flow shop scheduling problem under machine availability constraints. The machines are subject to flexible preventive maintenance activities. The nonresumable scenario for the jobs was considered. That is, when a job is interrupted by an unavailability period of a machine it should be restarted from the beginning. The objective is to minimize the total tardiness time for the jobs and the advance/tardiness for the maintenance activities. To solve the problem, a genetic algorithm was developed and successfully tested and validated on many problem instances. The computational results showed that the new genetic algorithm outperforms another earlier proposed algorithm. </p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Flow%20shop%20scheduling" title="Flow shop scheduling">Flow shop scheduling</a>, <a href="https://publications.waset.org/search?q=maintenance" title=" maintenance"> maintenance</a>, <a href="https://publications.waset.org/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/search?q=priority%20rules." title=" priority rules."> priority rules.</a> </p> <a href="https://publications.waset.org/10002533/a-genetic-algorithm-to-schedule-the-flow-shop-problem-under-preventive-maintenance-activities" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10002533/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10002533/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10002533/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10002533/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10002533/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10002533/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10002533/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10002533/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10002533/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10002533/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10002533.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1922</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3613</span> A Genetic Based Algorithm to Generate Random Simple Polygons Using a New Polygon Merge Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Ali%20Nourollah">Ali Nourollah</a>, <a href="https://publications.waset.org/search?q=Mohsen%20Movahedinejad"> Mohsen Movahedinejad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>In this paper a new algorithm to generate random simple polygons from a given set of points in a two dimensional plane is designed. The proposed algorithm uses a genetic algorithm to generate polygons with few vertices. A new merge algorithm is presented which converts any two polygons into a simple polygon. This algorithm at first changes two polygons into a polygonal chain and then the polygonal chain is converted into a simple polygon. The process of converting a polygonal chain into a simple polygon is based on the removal of intersecting edges. The experiments results show that the proposed algorithm has the ability to generate a great number of different simple polygons and has better performance in comparison to celebrated algorithms such as space partitioning and steady growth.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Divide%20and%20conquer" title="Divide and conquer">Divide and conquer</a>, <a href="https://publications.waset.org/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/search?q=merge%0D%0Apolygons" title=" merge polygons"> merge polygons</a>, <a href="https://publications.waset.org/search?q=Random%20simple%20polygon%20generation." title=" Random simple polygon generation."> Random simple polygon generation.</a> </p> <a href="https://publications.waset.org/10000366/a-genetic-based-algorithm-to-generate-random-simple-polygons-using-a-new-polygon-merge-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10000366/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10000366/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10000366/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10000366/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10000366/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10000366/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10000366/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10000366/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10000366/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10000366/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10000366.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">3290</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3612</span> Genetic Algorithm Approach for Solving the Falkner鈥揝kan Equation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Indu%20Saini">Indu Saini</a>, <a href="https://publications.waset.org/search?q=Phool%20Singh"> Phool Singh</a>, <a href="https://publications.waset.org/search?q=Vikas%20Malik"> Vikas Malik </a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>A novel method based on Genetic Algorithm to solve the boundary value problems (BVPs) of the Falkner–Skan equation over a semi-infinite interval has been presented. In our approach, we use the free boundary formulation to truncate the semi-infinite interval into a finite one. Then we use the shooting method based on Genetic Algorithm to transform the BVP into initial value problems (IVPs). Genetic Algorithm is used to calculate shooting angle. The initial value problems arisen during shooting are computed by Runge-Kutta Fehlberg method. The numerical solutions obtained by the present method are in agreement with those obtained by previous authors.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Boundary%20Layer%20Flow" title="Boundary Layer Flow">Boundary Layer Flow</a>, <a href="https://publications.waset.org/search?q=Falkner%E2%80%93Skan%20equation" title=" Falkner鈥揝kan equation"> Falkner鈥揝kan equation</a>, <a href="https://publications.waset.org/search?q=Genetic%20Algorithm" title=" Genetic Algorithm"> Genetic Algorithm</a>, <a href="https://publications.waset.org/search?q=Shooting%20method." title=" Shooting method. "> Shooting method. </a> </p> <a href="https://publications.waset.org/17407/genetic-algorithm-approach-for-solving-the-falkner-skan-equation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/17407/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/17407/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/17407/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/17407/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/17407/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/17407/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/17407/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/17407/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/17407/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/17407/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/17407.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">2509</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3611</span> Simulated Annealing and Genetic Algorithm in Telecommunications Network Planning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Aleksandar%20Tsenov">Aleksandar Tsenov</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The main goal of this work is to propose a way for combined use of two nontraditional algorithms by solving topological problems on telecommunications concentrator networks. The algorithms suggested are the Simulated Annealing algorithm and the Genetic Algorithm. The Algorithm of Simulated Annealing unifies the well known local search algorithms. In addition - Simulated Annealing allows acceptation of moves in the search space witch lead to decisions with higher cost in order to attempt to overcome any local minima obtained. The Genetic Algorithm is a heuristic approach witch is being used in wide areas of optimization works. In the last years this approach is also widely implemented in Telecommunications Networks Planning. In order to solve less or more complex planning problem it is important to find the most appropriate parameters for initializing the function of the algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Concentrator%20network" title="Concentrator network">Concentrator network</a>, <a href="https://publications.waset.org/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/search?q=simulated%0Aannealing" title=" simulated annealing"> simulated annealing</a>, <a href="https://publications.waset.org/search?q=UCPL." title=" UCPL."> UCPL.</a> </p> <a href="https://publications.waset.org/1350/simulated-annealing-and-genetic-algorithm-in-telecommunications-network-planning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/1350/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/1350/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/1350/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/1350/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/1350/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/1350/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/1350/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/1350/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/1350/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/1350/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/1350.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1724</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3610</span> An Analysis of Genetic Algorithm Based Test Data Compression Using Modified PRL Coding</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=K.%20S.%20Neelukumari">K. S. Neelukumari</a>, <a href="https://publications.waset.org/search?q=K.%20B.%20Jayanthi"> K. B. Jayanthi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper genetic based test data compression is targeted for improving the compression ratio and for reducing the computation time. The genetic algorithm is based on extended pattern run-length coding. The test set contains a large number of X value that can be effectively exploited to improve the test data compression. In this coding method, a reference pattern is set and its compatibility is checked. For this process, a genetic algorithm is proposed to reduce the computation time of encoding algorithm. This coding technique encodes the 2n compatible pattern or the inversely compatible pattern into a single test data segment or multiple test data segment. The experimental result shows that the compression ratio and computation time is reduced. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Backtracking" title="Backtracking">Backtracking</a>, <a href="https://publications.waset.org/search?q=test%20data%20compression%20%28TDC%29" title=" test data compression (TDC)"> test data compression (TDC)</a>, <a href="https://publications.waset.org/search?q=x-filling" title=" x-filling"> x-filling</a>, <a href="https://publications.waset.org/search?q=x-propagating%20and%20genetic%20algorithm." title=" x-propagating and genetic algorithm."> x-propagating and genetic algorithm.</a> </p> <a href="https://publications.waset.org/10002865/an-analysis-of-genetic-algorithm-based-test-data-compression-using-modified-prl-coding" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10002865/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10002865/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10002865/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10002865/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10002865/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10002865/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10002865/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10002865/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10002865/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10002865/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10002865.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1870</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3609</span> Design and Bandwidth Allocation of Embedded ATM Networks using Genetic Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=H.%20El-Madbouly">H. El-Madbouly</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, genetic algorithm (GA) is proposed for the design of an optimization algorithm to achieve the bandwidth allocation of ATM network. In Broadband ISDN, the ATM is a highbandwidth; fast packet switching and multiplexing technique. Using ATM it can be flexibly reconfigure the network and reassign the bandwidth to meet the requirements of all types of services. By dynamically routing the traffic and adjusting the bandwidth assignment, the average packet delay of the whole network can be reduced to a minimum. M/M/1 model can be used to analyze the performance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Bandwidth%20allocation" title="Bandwidth allocation">Bandwidth allocation</a>, <a href="https://publications.waset.org/search?q=Genetic%20algorithm" title=" Genetic algorithm"> Genetic algorithm</a>, <a href="https://publications.waset.org/search?q=ATMNetwork" title=" ATMNetwork"> ATMNetwork</a>, <a href="https://publications.waset.org/search?q=packet%20delay." title=" packet delay."> packet delay.</a> </p> <a href="https://publications.waset.org/1615/design-and-bandwidth-allocation-of-embedded-atm-networks-using-genetic-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/1615/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/1615/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/1615/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/1615/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/1615/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/1615/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/1615/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/1615/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/1615/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/1615/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/1615.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1376</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3608</span> Optimal DG Allocation in Distribution Network</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=A.%20Safari">A. Safari</a>, <a href="https://publications.waset.org/search?q=R.%20Jahani"> R. Jahani</a>, <a href="https://publications.waset.org/search?q=H.%20A.%20Shayanfar"> H. A. Shayanfar</a>, <a href="https://publications.waset.org/search?q=J.%20Olamaei"> J. Olamaei</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper shows the results obtained in the analysis of the impact of distributed generation (DG) on distribution losses and presents a new algorithm to the optimal allocation of distributed generation resources in distribution networks. The optimization is based on a Hybrid Genetic Algorithm and Particle Swarm Optimization (HGAPSO) aiming to optimal DG allocation in distribution network. Through this algorithm a significant improvement in the optimization goal is achieved. With a numerical example the superiority of the proposed algorithm is demonstrated in comparison with the simple genetic algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Distributed%20Generation" title="Distributed Generation">Distributed Generation</a>, <a href="https://publications.waset.org/search?q=Distribution%20Networks" title=" Distribution Networks"> Distribution Networks</a>, <a href="https://publications.waset.org/search?q=Genetic%20Algorithm" title="Genetic Algorithm">Genetic Algorithm</a>, <a href="https://publications.waset.org/search?q=Particle%20Swarm%20Optimization." title=" Particle Swarm Optimization."> Particle Swarm Optimization.</a> </p> <a href="https://publications.waset.org/12005/optimal-dg-allocation-in-distribution-network" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/12005/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/12005/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/12005/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/12005/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/12005/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/12005/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/12005/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/12005/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/12005/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/12005/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/12005.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">2704</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3607</span> An Enhanced Cryptanalytic Attack on Knapsack Cipher using Genetic Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Poonam%20Garg">Poonam Garg</a>, <a href="https://publications.waset.org/search?q=Aditya%20Shastri"> Aditya Shastri</a>, <a href="https://publications.waset.org/search?q=D.C.%20Agarwal"> D.C. Agarwal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> With the exponential growth of networked system and application such as eCommerce, the demand for effective internet security is increasing. Cryptology is the science and study of systems for secret communication. It consists of two complementary fields of study: cryptography and cryptanalysis. The application of genetic algorithms in the cryptanalysis of knapsack ciphers is suggested by Spillman [7]. In order to improve the efficiency of genetic algorithm attack on knapsack cipher, the previously published attack was enhanced and re-implemented with variation of initial assumptions and results are compared with Spillman results. The experimental result of research indicates that the efficiency of genetic algorithm attack on knapsack cipher can be improved with variation of initial assumption. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Genetic%20Algorithm" title="Genetic Algorithm">Genetic Algorithm</a>, <a href="https://publications.waset.org/search?q=Knapsack%20cipher" title=" Knapsack cipher"> Knapsack cipher</a>, <a href="https://publications.waset.org/search?q=Key%20search." title=" Key search."> Key search.</a> </p> <a href="https://publications.waset.org/2028/an-enhanced-cryptanalytic-attack-on-knapsack-cipher-using-genetic-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/2028/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/2028/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/2028/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/2028/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/2028/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/2028/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/2028/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/2028/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/2028/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/2028/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/2028.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1697</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3606</span> Optimal Control Problem, Quasi-Assignment Problem and Genetic Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Omid%20S.%20Fard">Omid S. Fard</a>, <a href="https://publications.waset.org/search?q=Akbar%20H.%20Borzabadi"> Akbar H. Borzabadi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper we apply one of approaches in category of heuristic methods as Genetic Algorithms for obtaining approximate solution of optimal control problems. The firs we convert optimal control problem to a quasi Assignment Problem by defining some usual characters as defined in Genetic algorithm applications. Then we obtain approximate optimal control function as an piecewise constant function. Finally the numerical examples are given. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Optimal%20control" title="Optimal control">Optimal control</a>, <a href="https://publications.waset.org/search?q=Integer%20programming" title=" Integer programming"> Integer programming</a>, <a href="https://publications.waset.org/search?q=Genetic%20algorithm" title=" Genetic algorithm"> Genetic algorithm</a>, <a href="https://publications.waset.org/search?q=Discrete%20approximation" title=" Discrete approximation"> Discrete approximation</a>, <a href="https://publications.waset.org/search?q=Linear%20programming." title=" Linear programming."> Linear programming.</a> </p> <a href="https://publications.waset.org/15413/optimal-control-problem-quasi-assignment-problem-and-genetic-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/15413/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> 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