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problem</title> <meta name="description" content="Search results for: EULR problem"> <meta name="keywords" content="EULR problem"> <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 navbar-toggler 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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="EULR problem"> <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> 7167</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: EULR problem</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7167</span> A Method for Improving the Embedded Runge Kutta Fehlberg 4(5)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sunyoung%20Bu">Sunyoung Bu</a>, <a href="https://publications.waset.org/abstracts/search?q=Wonkyu%20Chung"> Wonkyu Chung</a>, <a href="https://publications.waset.org/abstracts/search?q=Philsu%20Kim"> Philsu Kim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we introduce a method for improving the embedded Runge-Kutta-Fehlberg 4(5) method. At each integration step, the proposed method is comprised of two equations for the solution and the error, respectively. This solution and error are obtained by solving an initial value problem whose solution has the information of the error at each integration step. The constructed algorithm controls both the error and the time step size simultaneously and possesses a good performance in the computational cost compared to the original method. For the assessment of the effectiveness, EULR problem is numerically solved. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=embedded%20Runge-Kutta-Fehlberg%20method" title="embedded Runge-Kutta-Fehlberg method">embedded Runge-Kutta-Fehlberg method</a>, <a href="https://publications.waset.org/abstracts/search?q=initial%20value%20problem" title=" initial value problem"> initial value problem</a>, <a href="https://publications.waset.org/abstracts/search?q=EULR%20problem" title=" EULR problem"> EULR problem</a>, <a href="https://publications.waset.org/abstracts/search?q=integration%20step" title=" integration step"> integration step</a> </p> <a href="https://publications.waset.org/abstracts/12924/a-method-for-improving-the-embedded-runge-kutta-fehlberg-45" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/12924.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">463</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7166</span> Solving the Transportation Problem for Warehouses and Dealers in Bangalore City</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20Aditya">S. Aditya</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20T.%20Nideesh"> K. T. Nideesh</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20Guruprasad"> N. Guruprasad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Being a subclass of linear programing problem, the Transportation Problem is a classic Operations Research problem where the objective is to determine the schedule for transporting goods from source to destination in a way that minimizes the shipping cost while satisfying supply and demand constraints. In this paper, we are representing the transportation problem for various warehouses along with various dealers situated in Bangalore city to reduce the transportation cost incurred by them as of now. The problem is solved by obtaining the Initial Basic feasible Solution through various methods and further proceeding to obtain optimal cost. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=NW%20method" title="NW method">NW method</a>, <a href="https://publications.waset.org/abstracts/search?q=optimum%20utilization" title=" optimum utilization"> optimum utilization</a>, <a href="https://publications.waset.org/abstracts/search?q=transportation%20problem" title=" transportation problem"> transportation problem</a>, <a href="https://publications.waset.org/abstracts/search?q=Vogel%E2%80%99s%20approximation%20method" title=" Vogel’s approximation method"> Vogel’s approximation method</a> </p> <a href="https://publications.waset.org/abstracts/19160/solving-the-transportation-problem-for-warehouses-and-dealers-in-bangalore-city" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19160.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">438</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7165</span> Using Convergent and Divergent Thinking in Creative Problem Solving in Mathematics</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Keng%20Keh%20Lim">Keng Keh Lim</a>, <a href="https://publications.waset.org/abstracts/search?q=Zaleha%20Ismail"> Zaleha Ismail</a>, <a href="https://publications.waset.org/abstracts/search?q=Yudariah%20Mohammad%20Yusof"> Yudariah Mohammad Yusof</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper aims to find out how students using convergent and divergent thinking in creative problem solving to solve mathematical problems creatively. Eight engineering undergraduates in a local university took part in this study. They were divided into two groups. They solved the mathematical problems with the use of creative problem solving skills. Their solutions were collected and analyzed to reveal all the processes of problem solving, namely: problem definition, ideas generation, ideas evaluation, ideas judgment, and solution implementation. The result showed that the students were able to solve the mathematical problem with the use of creative problem solving skills. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=convergent%20thinking" title="convergent thinking">convergent thinking</a>, <a href="https://publications.waset.org/abstracts/search?q=divergent%20thinking" title=" divergent thinking"> divergent thinking</a>, <a href="https://publications.waset.org/abstracts/search?q=creative%20problem%20solving" title=" creative problem solving"> creative problem solving</a>, <a href="https://publications.waset.org/abstracts/search?q=creativity" title=" creativity"> creativity</a> </p> <a href="https://publications.waset.org/abstracts/77631/using-convergent-and-divergent-thinking-in-creative-problem-solving-in-mathematics" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/77631.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">349</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7164</span> Fuzzy Vehicle Routing Problem for Extreme Environment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=G.%20Sirbiladze">G. Sirbiladze</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20Ghvaberidze"> B. Ghvaberidze</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20Matsaberidze"> B. Matsaberidze</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A fuzzy vehicle routing problem is considered in the possibilistic environment. A new criterion, maximization of expectation of reliability for movement on closed routes is constructed. The objective of the research is to implement a two-stage scheme for solution of this problem. Based on the algorithm of preferences on the first stage, the sample of so-called “promising” routes will be selected. On the second stage, for the selected promising routes new bi-criteria problem will be solved - minimization of total traveled distance and maximization of reliability of routes. The problem will be stated as a fuzzy-partitioning problem. Two possible solutions of this scheme are considered. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=vehicle%20routing%20problem" title="vehicle routing problem">vehicle routing problem</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20partitioning%20problem" title=" fuzzy partitioning problem"> fuzzy partitioning problem</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple-criteria%20optimization" title=" multiple-criteria optimization"> multiple-criteria optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=possibility%20theory" title=" possibility theory"> possibility theory</a> </p> <a href="https://publications.waset.org/abstracts/9460/fuzzy-vehicle-routing-problem-for-extreme-environment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9460.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">547</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7163</span> Partial Knowledge Transfer Between the Source Problem and the Target Problem in Genetic Algorithms</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Terence%20Soule">Terence Soule</a>, <a href="https://publications.waset.org/abstracts/search?q=Tami%20Al%20Ghamdi"> Tami Al Ghamdi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> To study how the partial knowledge transfer may affect the Genetic Algorithm (GA) performance, we model the Transfer Learning (TL) process using GA as the model solver. The objective of the TL is to transfer the knowledge from one problem to another related problem. This process imitates how humans think in their daily life. In this paper, we proposed to study a case where the knowledge transferred from the S problem has less information than what the T problem needs. We sampled the transferred population using different strategies of TL. The results showed transfer part of the knowledge is helpful and speeds the GA process of finding a solution to the problem. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=transfer%20learning" title="transfer learning">transfer learning</a>, <a href="https://publications.waset.org/abstracts/search?q=partial%20transfer" title=" partial transfer"> partial transfer</a>, <a href="https://publications.waset.org/abstracts/search?q=evolutionary%20computation" title=" evolutionary computation"> evolutionary computation</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a> </p> <a href="https://publications.waset.org/abstracts/147924/partial-knowledge-transfer-between-the-source-problem-and-the-target-problem-in-genetic-algorithms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/147924.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">132</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7162</span> Bee Colony Optimization Applied to the Bin Packing Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kenza%20Aida%20Amara">Kenza Aida Amara</a>, <a href="https://publications.waset.org/abstracts/search?q=Bachir%20Djebbar"> Bachir Djebbar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We treat the two-dimensional bin packing problem which involves packing a given set of rectangles into a minimum number of larger identical rectangles called bins. This combinatorial problem is NP-hard. We propose a pretreatment for the oriented version of the problem that allows the valorization of the lost areas in the bins and the reduction of the size problem. A heuristic method based on the strategy first-fit adapted to this problem is presented. We present an approach of resolution by bee colony optimization. Computational results express a comparison of the number of bins used with and without pretreatment. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bee%20colony%20optimization" title="bee colony optimization">bee colony optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=bin%20packing" title=" bin packing"> bin packing</a>, <a href="https://publications.waset.org/abstracts/search?q=heuristic%20algorithm" title=" heuristic algorithm"> heuristic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=pretreatment" title=" pretreatment"> pretreatment</a> </p> <a href="https://publications.waset.org/abstracts/65005/bee-colony-optimization-applied-to-the-bin-packing-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/65005.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">634</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7161</span> A Method for Solving a Bi-Objective Transportation Problem under Fuzzy Environment </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sukhveer%20Singh">Sukhveer Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Sandeep%20Singh"> Sandeep Singh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A bi-objective fuzzy transportation problem with the objectives to minimize the total fuzzy cost and fuzzy time of transportation without according priorities to them is considered. To the best of our knowledge, there is no method in the literature to find efficient solutions of the bi-objective transportation problem under uncertainty. In this paper, a bi-objective transportation problem in an uncertain environment has been formulated. An algorithm has been proposed to find efficient solutions of the bi-objective transportation problem under uncertainty. The proposed algorithm avoids the degeneracy and gives the optimal solution faster than other existing algorithms for the given uncertain transportation problem. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=uncertain%20transportation%20problem" title="uncertain transportation problem">uncertain transportation problem</a>, <a href="https://publications.waset.org/abstracts/search?q=efficient%20solution" title=" efficient solution"> efficient solution</a>, <a href="https://publications.waset.org/abstracts/search?q=ranking%20function" title=" ranking function"> ranking function</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20transportation%20problem" title=" fuzzy transportation problem"> fuzzy transportation problem</a> </p> <a href="https://publications.waset.org/abstracts/73312/a-method-for-solving-a-bi-objective-transportation-problem-under-fuzzy-environment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/73312.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">525</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7160</span> Cooperative Coevolution for Neuro-Evolution of Feed Forward Networks for Time Series Prediction Using Hidden Neuron Connections</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ravneil%20Nand">Ravneil Nand</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Cooperative coevolution uses problem decomposition methods to solve a larger problem. The problem decomposition deals with breaking down the larger problem into a number of smaller sub-problems depending on their method. Different problem decomposition methods have their own strengths and limitations depending on the neural network used and application problem. In this paper we are introducing a new problem decomposition method known as Hidden-Neuron Level Decomposition (HNL). The HNL method is competing with established problem decomposition method in time series prediction. The results show that the proposed approach has improved the results in some benchmark data sets when compared to the standalone method and has competitive results when compared to methods from literature. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cooperative%20coevaluation" title="cooperative coevaluation">cooperative coevaluation</a>, <a href="https://publications.waset.org/abstracts/search?q=feed%20forward%20network" title=" feed forward network"> feed forward network</a>, <a href="https://publications.waset.org/abstracts/search?q=problem%20decomposition" title=" problem decomposition"> problem decomposition</a>, <a href="https://publications.waset.org/abstracts/search?q=neuron" title=" neuron"> neuron</a>, <a href="https://publications.waset.org/abstracts/search?q=synapse" title=" synapse"> synapse</a> </p> <a href="https://publications.waset.org/abstracts/29237/cooperative-coevolution-for-neuro-evolution-of-feed-forward-networks-for-time-series-prediction-using-hidden-neuron-connections" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/29237.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">335</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7159</span> Solution of Nonlinear Fractional Programming Problem with Bounded Parameters</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mrinal%20Jana">Mrinal Jana</a>, <a href="https://publications.waset.org/abstracts/search?q=Geetanjali%20Panda"> Geetanjali Panda</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper a methodology is developed to solve a nonlinear fractional programming problem in which the coefficients of the objective function and constraints are interval parameters. This model is transformed into a general optimization problem and relation between the original problem and the transformed problem is established. Finally the proposed methodology is illustrated through a numerical example. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fractional%20programming" title="fractional programming">fractional programming</a>, <a href="https://publications.waset.org/abstracts/search?q=interval%20valued%20function" title=" interval valued function"> interval valued function</a>, <a href="https://publications.waset.org/abstracts/search?q=interval%20inequalities" title=" interval inequalities"> interval inequalities</a>, <a href="https://publications.waset.org/abstracts/search?q=partial%20order%20relation" title=" partial order relation"> partial order relation</a> </p> <a href="https://publications.waset.org/abstracts/22261/solution-of-nonlinear-fractional-programming-problem-with-bounded-parameters" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/22261.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">519</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7158</span> Exhaustive Study of Essential Constraint Satisfaction Problem Techniques Based on N-Queens Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Md.%20Ahsan%20Ayub">Md. Ahsan Ayub</a>, <a href="https://publications.waset.org/abstracts/search?q=Kazi%20A.%20Kalpoma"> Kazi A. Kalpoma</a>, <a href="https://publications.waset.org/abstracts/search?q=Humaira%20Tasnim%20Proma"> Humaira Tasnim Proma</a>, <a href="https://publications.waset.org/abstracts/search?q=Syed%20Mehrab%20Kabir"> Syed Mehrab Kabir</a>, <a href="https://publications.waset.org/abstracts/search?q=Rakib%20Ibna%20Hamid%20Chowdhury"> Rakib Ibna Hamid Chowdhury</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Constraint Satisfaction Problem (CSP) is observed in various applications, i.e., scheduling problems, timetabling problems, assignment problems, etc. Researchers adopt a CSP technique to tackle a certain problem; however, each technique follows different approaches and ways to solve a problem network. In our exhaustive study, it has been possible to visualize the processes of essential CSP algorithms from a very concrete constraint satisfaction example, NQueens Problem, in order to possess a deep understanding about how a particular constraint satisfaction problem will be dealt with by our studied and implemented techniques. Besides, benchmark results - time vs. value of N in N-Queens - have been generated from our implemented approaches, which help understand at what factor each algorithm produces solutions; especially, in N-Queens puzzle. Thus, extended decisions can be made to instantiate a real life problem within CSP’s framework. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=arc%20consistency%20%28AC%29" title="arc consistency (AC)">arc consistency (AC)</a>, <a href="https://publications.waset.org/abstracts/search?q=backjumping%20algorithm%20%28BJ%29" title=" backjumping algorithm (BJ)"> backjumping algorithm (BJ)</a>, <a href="https://publications.waset.org/abstracts/search?q=backtracking%20algorithm%20%28BT%29" title=" backtracking algorithm (BT)"> backtracking algorithm (BT)</a>, <a href="https://publications.waset.org/abstracts/search?q=constraint%20satisfaction%20problem%20%28CSP%29" title=" constraint satisfaction problem (CSP)"> constraint satisfaction problem (CSP)</a>, <a href="https://publications.waset.org/abstracts/search?q=forward%20checking%20%28FC%29" title=" forward checking (FC)"> forward checking (FC)</a>, <a href="https://publications.waset.org/abstracts/search?q=least%20constrained%20values%20%28LCV%29" title=" least constrained values (LCV)"> least constrained values (LCV)</a>, <a href="https://publications.waset.org/abstracts/search?q=maintaining%20arc%20consistency%20%28MAC%29" title=" maintaining arc consistency (MAC)"> maintaining arc consistency (MAC)</a>, <a href="https://publications.waset.org/abstracts/search?q=minimum%20remaining%20values%20%28MRV%29" title=" minimum remaining values (MRV)"> minimum remaining values (MRV)</a>, <a href="https://publications.waset.org/abstracts/search?q=N-Queens%20problem" title=" N-Queens problem"> N-Queens problem</a> </p> <a href="https://publications.waset.org/abstracts/69933/exhaustive-study-of-essential-constraint-satisfaction-problem-techniques-based-on-n-queens-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/69933.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">364</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7157</span> Explicit Iterative Scheme for Approximating a Common Solution of Generalized Mixed Equilibrium Problem and Fixed Point Problem for a Nonexpansive Semigroup in Hilbert Space</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Farid">Mohammad Farid</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we introduce and study an explicit iterative method based on hybrid extragradient method to approximate a common solution of generalized mixed equilibrium problem and fixed point problem for a nonexpansive semigroup in Hilbert space. Further, we prove that the sequence generated by the proposed iterative scheme converge strongly to the common solution of generalized mixed equilibrium problem and fixed point problem for a nonexpansive semigroup. This common solution is the unique solution of a variational inequality problem and is the optimality condition for a minimization problem. The results presented in this paper are the supplement, extension and generalization of the previously known results in this area. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=generalized%20mixed%20equilibrium%20problem" title="generalized mixed equilibrium problem">generalized mixed equilibrium problem</a>, <a href="https://publications.waset.org/abstracts/search?q=fixed-point%20problem" title=" fixed-point problem"> fixed-point problem</a>, <a href="https://publications.waset.org/abstracts/search?q=nonexpansive%20semigroup" title=" nonexpansive semigroup"> nonexpansive semigroup</a>, <a href="https://publications.waset.org/abstracts/search?q=variational%20inequality%20problem" title=" variational inequality problem"> variational inequality problem</a>, <a href="https://publications.waset.org/abstracts/search?q=iterative%20algorithms" title=" iterative algorithms"> iterative algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=hybrid%20extragradient%20method" title=" hybrid extragradient method"> hybrid extragradient method</a> </p> <a href="https://publications.waset.org/abstracts/14070/explicit-iterative-scheme-for-approximating-a-common-solution-of-generalized-mixed-equilibrium-problem-and-fixed-point-problem-for-a-nonexpansive-semigroup-in-hilbert-space" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14070.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">475</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7156</span> Regret-Regression for Multi-Armed Bandit Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Deyadeen%20Ali%20Alshibani">Deyadeen Ali Alshibani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In the literature, the multi-armed bandit problem as a statistical decision model of an agent trying to optimize his decisions while improving his information at the same time. There are several different algorithms models and their applications on this problem. In this paper, we evaluate the Regret-regression through comparing with Q-learning method. A simulation on determination of optimal treatment regime is presented in detail. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=optimal" title="optimal">optimal</a>, <a href="https://publications.waset.org/abstracts/search?q=bandit%20problem" title=" bandit problem"> bandit problem</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=dynamic%20programming" title=" dynamic programming"> dynamic programming</a> </p> <a href="https://publications.waset.org/abstracts/18593/regret-regression-for-multi-armed-bandit-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18593.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">453</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7155</span> A Fuzzy Programming Approach for Solving Intuitionistic Fuzzy Linear Fractional Programming Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sujeet%20Kumar%20Singh">Sujeet Kumar Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Shiv%20Prasad%20Yadav"> Shiv Prasad Yadav</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper develops an approach for solving intuitionistic fuzzy linear fractional programming (IFLFP) problem where the cost of the objective function, the resources, and the technological coefficients are triangular intuitionistic fuzzy numbers. Here, the IFLFP problem is transformed into an equivalent crisp multi-objective linear fractional programming (MOLFP) problem. By using fuzzy mathematical programming approach the transformed MOLFP problem is reduced into a single objective linear programming (LP) problem. The proposed procedure is illustrated through a numerical example. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=triangular%20intuitionistic%20fuzzy%20number" title="triangular intuitionistic fuzzy number">triangular intuitionistic fuzzy number</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20programming%20problem" title=" linear programming problem"> linear programming problem</a>, <a href="https://publications.waset.org/abstracts/search?q=multi%20objective%20linear%20programming%20problem" title=" multi objective linear programming problem"> multi objective linear programming problem</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20mathematical%20programming" title=" fuzzy mathematical programming"> fuzzy mathematical programming</a>, <a href="https://publications.waset.org/abstracts/search?q=membership%20function" title=" membership function"> membership function</a> </p> <a href="https://publications.waset.org/abstracts/16411/a-fuzzy-programming-approach-for-solving-intuitionistic-fuzzy-linear-fractional-programming-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16411.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">566</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7154</span> The Algorithm to Solve the Extend General Malfatti’s Problem in a Convex Circular Triangle</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ching-Shoei%20Chiang">Ching-Shoei Chiang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Malfatti’s Problem solves the problem of fitting 3 circles into a right triangle such that these 3 circles are tangent to each other, and each circle is also tangent to a pair of the triangle’s sides. This problem has been extended to any triangle (called general Malfatti’s Problem). Furthermore, the problem has been extended to have 1+2+…+n circles inside the triangle with special tangency properties among circles and triangle sides; we call it extended general Malfatti’s problem. In the extended general Malfatti’s problem, call it Tri(Tn), where Tn is the triangle number, there are closed-form solutions for Tri(T₁) (inscribed circle) problem and Tri(T₂) (3 Malfatti’s circles) problem. These problems become more complex when n is greater than 2. In solving Tri(Tn) problem, n>2, algorithms have been proposed to solve these problems numerically. With a similar idea, this paper proposed an algorithm to find the radii of circles with the same tangency properties. Instead of the boundary of the triangle being a straight line, we use a convex circular arc as the boundary and try to find Tn circles inside this convex circular triangle with the same tangency properties among circles and boundary Carc. We call these problems the Carc(Tn) problems. The CPU time it takes for Carc(T16) problem, which finds 136 circles inside a convex circular triangle with specified tangency properties, is less than one second. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=circle%20packing" title="circle packing">circle packing</a>, <a href="https://publications.waset.org/abstracts/search?q=computer-aided%20geometric%20design" title=" computer-aided geometric design"> computer-aided geometric design</a>, <a href="https://publications.waset.org/abstracts/search?q=geometric%20constraint%20solver" title=" geometric constraint solver"> geometric constraint solver</a>, <a href="https://publications.waset.org/abstracts/search?q=Malfatti%E2%80%99s%20problem" title=" Malfatti’s problem"> Malfatti’s problem</a> </p> <a href="https://publications.waset.org/abstracts/165851/the-algorithm-to-solve-the-extend-general-malfattis-problem-in-a-convex-circular-triangle" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/165851.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">110</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7153</span> Ubiquitous Scaffold Learning Environment Using Problem-based Learning Activities to Enhance Problem-solving Skills and Context Awareness </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Noppadon%20Phumeechanya">Noppadon Phumeechanya</a>, <a href="https://publications.waset.org/abstracts/search?q=Panita%20Wannapiroon"> Panita Wannapiroon</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The purpose of this research is to design the ubiquitous scaffold learning environment using problem-based learning activities that enhance problem-solving skills and context awareness, and to evaluate the suitability of the ubiquitous scaffold learning environment using problem-based learning activities. We divide the research procedures into two phases. The first phase is to design the ubiquitous scaffold learning environment using problem-based learning activities, and the second is to evaluate the ubiquitous scaffold learning environment using problem-based learning activities. The sample group in this study consists of five experts selected using the purposive sampling method. We analyse data by arithmetic mean and standard deviation. The research findings are as follows; the ubiquitous scaffold learning environment using problem-based learning activities consists of three major steps, the first is preparation before learning. This prepares learners to acknowledge details and learn through u-LMS. The second is the learning process, where learning activities happen in the ubiquitous learning environment and learners learn online with scaffold systems for each step of problem solving. The third step is measurement and evaluation. The experts agree that the ubiquitous scaffold learning environment using problem-based learning activities is highly appropriate. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ubiquitous%20learning%20environment%20scaffolding" title="ubiquitous learning environment scaffolding">ubiquitous learning environment scaffolding</a>, <a href="https://publications.waset.org/abstracts/search?q=learning%20activities" title=" learning activities"> learning activities</a>, <a href="https://publications.waset.org/abstracts/search?q=problem-based%20learning" title=" problem-based learning"> problem-based learning</a>, <a href="https://publications.waset.org/abstracts/search?q=problem-solving%20skills" title=" problem-solving skills"> problem-solving skills</a>, <a href="https://publications.waset.org/abstracts/search?q=context%20awareness" title=" context awareness"> context awareness</a> </p> <a href="https://publications.waset.org/abstracts/30647/ubiquitous-scaffold-learning-environment-using-problem-based-learning-activities-to-enhance-problem-solving-skills-and-context-awareness" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/30647.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">498</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7152</span> Young Children’s Use of Representations in Problem Solving </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kamariah%20Abu%20Bakar">Kamariah Abu Bakar</a>, <a href="https://publications.waset.org/abstracts/search?q=Jennifer%20Way"> Jennifer Way</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study investigated how young children (six years old) constructed and used representations in mathematics classroom; particularly in problem solving. The purpose of this study is to explore the ways children used representations in solving addition problems and to determine whether their representations can play a supportive role in understanding the problem situation and solving them correctly. Data collection includes observations, children’s artifact, photographs and conversation with children during task completion. The results revealed that children were able to construct and use various representations in solving problems. However, they have certain preferences in generating representations to support their problem solving. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=young%20children" title="young children">young children</a>, <a href="https://publications.waset.org/abstracts/search?q=representations" title=" representations"> representations</a>, <a href="https://publications.waset.org/abstracts/search?q=addition" title=" addition"> addition</a>, <a href="https://publications.waset.org/abstracts/search?q=problem%20solving" title=" problem solving"> problem solving</a> </p> <a href="https://publications.waset.org/abstracts/40756/young-childrens-use-of-representations-in-problem-solving" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/40756.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">461</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7151</span> Two-Stage Approach for Solving the Multi-Objective Optimization Problem on Combinatorial Configurations</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Liudmyla%20Koliechkina">Liudmyla Koliechkina</a>, <a href="https://publications.waset.org/abstracts/search?q=Olena%20Dvirna"> Olena Dvirna</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The statement of the multi-objective optimization problem on combinatorial configurations is formulated, and the approach to its solution is proposed. The problem is of interest as a combinatorial optimization one with many criteria, which is a model of many applied tasks. The approach to solving the multi-objective optimization problem on combinatorial configurations consists of two stages; the first is the reduction of the multi-objective problem to the single criterion based on existing multi-objective optimization methods, the second stage solves the directly replaced single criterion combinatorial optimization problem by the horizontal combinatorial method. This approach provides the optimal solution to the multi-objective optimization problem on combinatorial configurations, taking into account additional restrictions for a finite number of steps. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=discrete%20set" title="discrete set">discrete set</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20combinatorial%20optimization" title=" linear combinatorial optimization"> linear combinatorial optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-objective%20optimization" title=" multi-objective optimization"> multi-objective optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=Pareto%20solutions" title=" Pareto solutions"> Pareto solutions</a>, <a href="https://publications.waset.org/abstracts/search?q=partial%20permutation%20set" title=" partial permutation set"> partial permutation set</a>, <a href="https://publications.waset.org/abstracts/search?q=structural%20graph" title=" structural graph"> structural graph</a> </p> <a href="https://publications.waset.org/abstracts/133824/two-stage-approach-for-solving-the-multi-objective-optimization-problem-on-combinatorial-configurations" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/133824.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">167</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7150</span> On Optimum Stratification</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20G.%20M.%20Khan">M. G. M. Khan</a>, <a href="https://publications.waset.org/abstracts/search?q=V.%20D.%20Prasad"> V. D. Prasad</a>, <a href="https://publications.waset.org/abstracts/search?q=D.%20K.%20Rao"> D. K. Rao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this manuscript, we discuss the problem of determining the optimum stratification of a study (or main) variable based on the auxiliary variable that follows a uniform distribution. If the stratification of survey variable is made using the auxiliary variable it may lead to substantial gains in precision of the estimates. This problem is formulated as a Nonlinear Programming Problem (NLPP), which turn out to multistage decision problem and is solved using dynamic programming technique. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=auxiliary%20variable" title="auxiliary variable">auxiliary variable</a>, <a href="https://publications.waset.org/abstracts/search?q=dynamic%20programming%20technique" title=" dynamic programming technique"> dynamic programming technique</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinear%20programming%20problem" title=" nonlinear programming problem"> nonlinear programming problem</a>, <a href="https://publications.waset.org/abstracts/search?q=optimum%20stratification" title=" optimum stratification"> optimum stratification</a>, <a href="https://publications.waset.org/abstracts/search?q=uniform%20distribution" title=" uniform distribution"> uniform distribution</a> </p> <a href="https://publications.waset.org/abstracts/6677/on-optimum-stratification" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6677.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">333</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7149</span> Genetic Algorithm for Solving the Flexible Job-Shop Scheduling Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Guilherme%20Baldo%20Carlos">Guilherme Baldo Carlos</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The flexible job-shop scheduling problem (FJSP) is an NP-hard combinatorial optimization problem, which can be applied to model several applications in a wide array of industries. This problem will have its importance increase due to the shift in the production mode that modern society is going through. The demands are increasing and for products personalized and customized. This work aims to apply a meta-heuristic called a genetic algorithm (GA) to solve this problem. A GA is a meta-heuristic inspired by the natural selection of Charles Darwin; it produces a population of individuals (solutions) and selects, mutates, and mates the individuals through generations in order to find a good solution for the problem. The results found indicate that the GA is suitable for FJSP solving. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title="genetic algorithm">genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=evolutionary%20algorithm" title=" evolutionary algorithm"> evolutionary algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=scheduling" title=" scheduling"> scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=flexible%20job-shop%20scheduling" title=" flexible job-shop scheduling"> flexible job-shop scheduling</a> </p> <a href="https://publications.waset.org/abstracts/132314/genetic-algorithm-for-solving-the-flexible-job-shop-scheduling-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/132314.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">147</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7148</span> Number Sense Proficiency and Problem Solving Performance of Grade Seven Students</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Laissa%20Mae%20Francisco">Laissa Mae Francisco</a>, <a href="https://publications.waset.org/abstracts/search?q=John%20Rolex%20Ingreso"> John Rolex Ingreso</a>, <a href="https://publications.waset.org/abstracts/search?q=Anna%20Krizel%20Menguito"> Anna Krizel Menguito</a>, <a href="https://publications.waset.org/abstracts/search?q=Criselda%20Robrigado"> Criselda Robrigado</a>, <a href="https://publications.waset.org/abstracts/search?q=Rej%20Maegan%20%20Tuazon"> Rej Maegan Tuazon</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study aims to determine and describe the existing relationship between number sense proficiency and problem-solving performance of grade seven students from Victorino Mapa High School, Manila. A paper pencil exam containing of 50-item number sense test and 5-item problem-solving test which measures their number sense proficiency and problem-solving performance adapted from McIntosh, Reys, and Bana were used as the research instruments. The data obtained from this study were interpreted and analyzed using the Pearson – Product Moment Coefficient of Correlation to determine the relationship between the two variables. It was found out that students who were low in number sense proficiency tend to be the students with poor problem-solving performance and students with medium number sense proficiency are most likely to have an average problem-solving performance. Likewise, students with high number sense proficiency are those who do excellently in problem-solving performance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=number%20sense" title="number sense">number sense</a>, <a href="https://publications.waset.org/abstracts/search?q=performance" title=" performance"> performance</a>, <a href="https://publications.waset.org/abstracts/search?q=problem%20solving" title=" problem solving"> problem solving</a>, <a href="https://publications.waset.org/abstracts/search?q=proficiency" title=" proficiency"> proficiency</a> </p> <a href="https://publications.waset.org/abstracts/59954/number-sense-proficiency-and-problem-solving-performance-of-grade-seven-students" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/59954.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">438</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7147</span> Incorporating Polya’s Problem Solving Process: A Polytechnic Mathematics Module Case Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pei%20Chin%20Lim">Pei Chin Lim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> School of Mathematics and Science of Singapore Polytechnic offers a Basic Mathematics module to students who did not pass GCE O-Level Additional Mathematics. These students are weaker in Mathematics. In particular, they struggle with word problems and tend to leave them blank in tests and examinations. In order to improve students’ problem-solving skills, the school redesigned the Basic Mathematics module to incorporate Polya’s problem-solving methodology. During tutorial lessons, students have to work through learning activities designed to raise their metacognitive awareness by following Polya’s problem-solving process. To assess the effectiveness of the redesign, students’ working for a challenging word problem in the mid-semester test were analyzed. Sixty-five percent of students attempted to understand the problem by making sketches. Twenty-eight percent of students went on to devise a plan and implement it. Only five percent of the students still left the question blank. These preliminary results suggest that with regular exposure to an explicit and systematic problem-solving approach, weak students’ problem-solving skills can potentially be improved. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=mathematics%20education" title="mathematics education">mathematics education</a>, <a href="https://publications.waset.org/abstracts/search?q=metacognition" title=" metacognition"> metacognition</a>, <a href="https://publications.waset.org/abstracts/search?q=problem%20solving" title=" problem solving"> problem solving</a>, <a href="https://publications.waset.org/abstracts/search?q=weak%20students" title=" weak students"> weak students</a> </p> <a href="https://publications.waset.org/abstracts/98195/incorporating-polyas-problem-solving-process-a-polytechnic-mathematics-module-case-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/98195.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">162</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7146</span> An Optimization Model for Maximum Clique Problem Based on Semidefinite Programming</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Derkaoui%20Orkia">Derkaoui Orkia</a>, <a href="https://publications.waset.org/abstracts/search?q=Lehireche%20Ahmed"> Lehireche Ahmed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The topic of this article is to exploring the potentialities of a powerful optimization technique, namely Semidefinite Programming, for solving NP-hard problems. This approach provides tight relaxations of combinatorial and quadratic problems. In this work, we solve the maximum clique problem using this relaxation. The clique problem is the computational problem of finding cliques in a graph. It is widely acknowledged for its many applications in real-world problems. The numerical results show that it is possible to find a maximum clique in polynomial time, using an algorithm based on semidefinite programming. We implement a primal-dual interior points algorithm to solve this problem based on semidefinite programming. The semidefinite relaxation of this problem can be solved in polynomial time. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=semidefinite%20programming" title="semidefinite programming">semidefinite programming</a>, <a href="https://publications.waset.org/abstracts/search?q=maximum%20clique%20problem" title=" maximum clique problem"> maximum clique problem</a>, <a href="https://publications.waset.org/abstracts/search?q=primal-dual%20interior%20point%20method" title=" primal-dual interior point method"> primal-dual interior point method</a>, <a href="https://publications.waset.org/abstracts/search?q=relaxation" title=" relaxation"> relaxation</a> </p> <a href="https://publications.waset.org/abstracts/73224/an-optimization-model-for-maximum-clique-problem-based-on-semidefinite-programming" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/73224.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">222</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7145</span> A New Graph Theoretic Problem with Ample Practical Applications</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mehmet%20Hakan%20Karaata">Mehmet Hakan Karaata</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we first coin a new graph theocratic problem with numerous applications. Second, we provide two algorithms for the problem. The first solution is using a brute-force techniques, whereas the second solution is based on an initial identification of the cycles in the given graph. We then provide a correctness proof of the algorithm. The applications of the problem include graph analysis, graph drawing and network structuring. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=algorithm" title="algorithm">algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=cycle" title=" cycle"> cycle</a>, <a href="https://publications.waset.org/abstracts/search?q=graph%20algorithm" title=" graph algorithm"> graph algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=graph%20theory" title=" graph theory"> graph theory</a>, <a href="https://publications.waset.org/abstracts/search?q=network%20structuring" title=" network structuring"> network structuring</a> </p> <a href="https://publications.waset.org/abstracts/67285/a-new-graph-theoretic-problem-with-ample-practical-applications" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/67285.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">386</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7144</span> Teaching and Learning Physics via GPS and WikiS</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hashini%20E.%20Mohottala">Hashini E. Mohottala</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We report the combine use of Wikispaces (WikiS) and Group Problem Solving (GPS) sessions conducted in the introductory level physics classes. As a part of this new teaching tool, some essay type problems were posted on the WikiS in weekly basis and students were encouraged to participate in problem solving without providing numerical final answers but the steps. Wikispace is used as a platform for students to meet online and create discussions. Each week students were further evaluated on problem solving skills opening up more opportunity for peer interaction through GPS. Each group was given a different problem to solve and the answers were graded. Students developed a set of skills in decision-making, problem solving, communication, negotiation, critical and independent thinking and teamwork through the combination of WikiS and GPS. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=group%20problem%20solving%20%28GPS%29" title="group problem solving (GPS)">group problem solving (GPS)</a>, <a href="https://publications.waset.org/abstracts/search?q=wikispace%20%28WikiS%29" title=" wikispace (WikiS)"> wikispace (WikiS)</a>, <a href="https://publications.waset.org/abstracts/search?q=physics%20education" title=" physics education"> physics education</a>, <a href="https://publications.waset.org/abstracts/search?q=learning" title=" learning"> learning</a> </p> <a href="https://publications.waset.org/abstracts/18720/teaching-and-learning-physics-via-gps-and-wikis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18720.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">418</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7143</span> Comparative Analysis of Two Different Ant Colony Optimization Algorithm for Solving Travelling Salesman Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sourabh%20Joshi">Sourabh Joshi</a>, <a href="https://publications.waset.org/abstracts/search?q=Tarun%20Sharma"> Tarun Sharma</a>, <a href="https://publications.waset.org/abstracts/search?q=Anurag%20Sharma"> Anurag Sharma</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Ant Colony Optimization is heuristic Algorithm which has been proven a successful technique applied on number of combinatorial optimization problems. Two variants of Ant Colony Optimization algorithm named Ant System and Max-Min Ant System are implemented in MATLAB to solve travelling Salesman Problem and the results are compared. In, this paper both systems are analyzed by solving the some Travelling Salesman Problem and depict which system solve the problem better in term of cost and time. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ant%20Colony%20Optimization" title="Ant Colony Optimization">Ant Colony Optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=Travelling%20Salesman%20Problem" title=" Travelling Salesman Problem"> Travelling Salesman Problem</a>, <a href="https://publications.waset.org/abstracts/search?q=Ant%20System" title=" Ant System"> Ant System</a>, <a href="https://publications.waset.org/abstracts/search?q=Max-Min%20Ant%20System" title=" Max-Min Ant System"> Max-Min Ant System</a> </p> <a href="https://publications.waset.org/abstracts/18457/comparative-analysis-of-two-different-ant-colony-optimization-algorithm-for-solving-travelling-salesman-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18457.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">483</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7142</span> On the Application of Heuristics of the Traveling Salesman Problem for the Task of Restoring the DNA Matrix</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Boris%20Melnikov">Boris Melnikov</a>, <a href="https://publications.waset.org/abstracts/search?q=Dmitrii%20Chaikovskii"> Dmitrii Chaikovskii</a>, <a href="https://publications.waset.org/abstracts/search?q=Elena%20Melnikova"> Elena Melnikova</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The traveling salesman problem (TSP) is a well-known optimization problem that seeks to find the shortest possible route that visits a set of points and returns to the starting point. In this paper, we apply some heuristics of the TSP for the task of restoring the DNA matrix. This restoration problem is often considered in biocybernetics. For it, we must recover the matrix of distances between DNA sequences if not all the elements of the matrix under consideration are known at the input. We consider the possibility of using this method in the testing of distance calculation algorithms between a pair of DNAs to restore the partially filled matrix. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=optimization%20problems" title="optimization problems">optimization problems</a>, <a href="https://publications.waset.org/abstracts/search?q=DNA%20matrix" title=" DNA matrix"> DNA matrix</a>, <a href="https://publications.waset.org/abstracts/search?q=partially%20filled%20matrix" title=" partially filled matrix"> partially filled matrix</a>, <a href="https://publications.waset.org/abstracts/search?q=traveling%20salesman%20problem" title=" traveling salesman problem"> traveling salesman problem</a>, <a href="https://publications.waset.org/abstracts/search?q=heuristic%20algorithms" title=" heuristic algorithms"> heuristic algorithms</a> </p> <a href="https://publications.waset.org/abstracts/172868/on-the-application-of-heuristics-of-the-traveling-salesman-problem-for-the-task-of-restoring-the-dna-matrix" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/172868.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">150</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7141</span> Transfer Knowledge From Multiple Source Problems to a Target Problem in Genetic Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Terence%20Soule">Terence Soule</a>, <a href="https://publications.waset.org/abstracts/search?q=Tami%20Al%20Ghamdi"> Tami Al Ghamdi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> To study how to transfer knowledge from multiple source problems to the target problem, we modeled the Transfer Learning (TL) process using Genetic Algorithms as the model solver. TL is the process that aims to transfer learned data from one problem to another problem. The TL process aims to help Machine Learning (ML) algorithms find a solution to the problems. The Genetic Algorithms (GA) give researchers access to information that we have about how the old problem is solved. In this paper, we have five different source problems, and we transfer the knowledge to the target problem. We studied different scenarios of the target problem. The results showed combined knowledge from multiple source problems improves the GA performance. Also, the process of combining knowledge from several problems results in promoting diversity of the transferred population. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=transfer%20learning" title="transfer learning">transfer learning</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=evolutionary%20computation" title=" evolutionary computation"> evolutionary computation</a>, <a href="https://publications.waset.org/abstracts/search?q=source%20and%20target" title=" source and target"> source and target</a> </p> <a href="https://publications.waset.org/abstracts/147927/transfer-knowledge-from-multiple-source-problems-to-a-target-problem-in-genetic-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/147927.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">140</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7140</span> Optimization of Maritime Platform Transport Problem of Solid, Special and Dangerous Waste</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ocotl%C3%A1n%20D%C3%ADaz-Parra">Ocotlán Díaz-Parra</a>, <a href="https://publications.waset.org/abstracts/search?q=Jorge%20A.%20Ruiz-Vanoye"> Jorge A. Ruiz-Vanoye</a>, <a href="https://publications.waset.org/abstracts/search?q=Alejandro%20Fuentes-Penna"> Alejandro Fuentes-Penna</a>, <a href="https://publications.waset.org/abstracts/search?q=Beatriz%20Bernabe-Loranca"> Beatriz Bernabe-Loranca</a>, <a href="https://publications.waset.org/abstracts/search?q=Patricia%20Ambrocio-Cruz"> Patricia Ambrocio-Cruz</a>, <a href="https://publications.waset.org/abstracts/search?q=Jos%C3%A9%20J.%20Hern%C3%A1ndez-Flores"> José J. Hernández-Flores</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Maritime Platform Transport Problem of Solid, Special and Dangerous Waste consist of to minimize the monetary value of carry different types of waste from one location to another location using ships. We offer a novel mathematical, the characterization of the problem and the use CPLEX to find the optimal values to solve the Solid, Special and Hazardous Waste Transportation Problem of offshore platforms instances of Mexican state-owned petroleum company (PEMEX). The set of instances used are WTPLib real instances and the tool CPLEX solver to solve the MPTPSSDW problem. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=oil%20platform" title="oil platform">oil platform</a>, <a href="https://publications.waset.org/abstracts/search?q=transport%20problem" title=" transport problem"> transport problem</a>, <a href="https://publications.waset.org/abstracts/search?q=waste" title=" waste"> waste</a>, <a href="https://publications.waset.org/abstracts/search?q=solid%20waste" title=" solid waste"> solid waste</a> </p> <a href="https://publications.waset.org/abstracts/42738/optimization-of-maritime-platform-transport-problem-of-solid-special-and-dangerous-waste" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/42738.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">471</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7139</span> An Improved Approach to Solve Two-Level Hierarchical Time Minimization Transportation Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kalpana%20Dahiya">Kalpana Dahiya</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper discusses a two-level hierarchical time minimization transportation problem, which is an important class of transportation problems arising in industries. This problem has been studied by various researchers, and a number of polynomial time iterative algorithms are available to find its solution. All the existing algorithms, though efficient, have some shortcomings. The current study proposes an alternate solution algorithm for the problem that is more efficient in terms of computational time than the existing algorithms. The results justifying the underlying theory of the proposed algorithm are given. Further, a detailed comparison of the computational behaviour of all the algorithms for randomly generated instances of this problem of different sizes validates the efficiency of the proposed algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=global%20optimization" title="global optimization">global optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=hierarchical%20optimization" title=" hierarchical optimization"> hierarchical optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=transportation%20problem" title=" transportation problem"> transportation problem</a>, <a href="https://publications.waset.org/abstracts/search?q=concave%20minimization" title=" concave minimization"> concave minimization</a> </p> <a href="https://publications.waset.org/abstracts/122713/an-improved-approach-to-solve-two-level-hierarchical-time-minimization-transportation-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/122713.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">162</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7138</span> Order Picking Problem: An Exact and Heuristic Algorithms for the Generalized Travelling Salesman Problem With Geographical Overlap Between Clusters</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Farzaneh%20Rajabighamchi">Farzaneh Rajabighamchi</a>, <a href="https://publications.waset.org/abstracts/search?q=Stan%20van%20Hoesel"> Stan van Hoesel</a>, <a href="https://publications.waset.org/abstracts/search?q=Christof%20Defryn"> Christof Defryn</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The generalized traveling salesman problem (GTSP) is an extension of the traveling salesman problem (TSP) where the set of nodes is partitioned into clusters, and the salesman must visit exactly one node per cluster. In this research, we apply the definition of the GTSP to an order picker routing problem with multiple locations per product. As such, each product represents a cluster and its corresponding nodes are the locations at which the product can be retrieved. To pick a certain product item from the warehouse, the picker needs to visit one of these locations during its pick tour. As all products are scattered throughout the warehouse, the product clusters not separated geographically. We propose an exact LP model as well as heuristic and meta-heuristic solution algorithms for the order picking problem with multiple product locations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=warehouse%20optimization" title="warehouse optimization">warehouse optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=order%20picking%20problem" title=" order picking problem"> order picking problem</a>, <a href="https://publications.waset.org/abstracts/search?q=generalised%20travelling%20salesman%20problem" title=" generalised travelling salesman problem"> generalised travelling salesman problem</a>, <a href="https://publications.waset.org/abstracts/search?q=heuristic%20algorithm" title=" heuristic algorithm"> heuristic algorithm</a> </p> <a href="https://publications.waset.org/abstracts/151459/order-picking-problem-an-exact-and-heuristic-algorithms-for-the-generalized-travelling-salesman-problem-with-geographical-overlap-between-clusters" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/151459.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">112</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=EULR%20problem&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=EULR%20problem&page=3">3</a></li> <li class="page-item"><a class="page-link" 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