Search results for: B. Matsaberidze

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Matsaberidze</title> <meta name="description" content="Search results for: B. Matsaberidze"> <meta name="keywords" content="B. Matsaberidze"> <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 ml-auto" type="button" data-toggle="collapse" data-target="#navbarMenu" aria-controls="navbarMenu" aria-expanded="false" aria-label="Toggle navigation"> <span class="navbar-toggler-icon"></span> </button> <div class="w-100"> <div class="d-none d-lg-flex flex-row-reverse"> <form method="get" action="https://waset.org/search" class="form-inline my-2 my-lg-0"> <input class="form-control mr-sm-2" type="search" placeholder="Search Conferences" value="B. 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Matsaberidze"> <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> 3</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: B. Matsaberidze</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3</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">2</span> Evidence Theory Based Emergency Multi-Attribute Group Decision-Making: Application in Facility Location Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bidzina%20Matsaberidze">Bidzina Matsaberidze</a> </p> <p class="card-text"><strong>Abstract:</strong></p> It is known that, in emergency situations, multi-attribute group decision-making (MAGDM) models are characterized by insufficient objective data and a lack of time to respond to the task. Evidence theory is an effective tool for describing such incomplete information in decision-making models when the expert and his knowledge are involved in the estimations of the MAGDM parameters. We consider an emergency decision-making model, where expert assessments on humanitarian aid from distribution centers (HADC) are represented in q-rung ortho-pair fuzzy numbers, and the data structure is described within the data body theory. Based on focal probability construction and experts’ evaluations, an objective function-distribution centers’ selection ranking index is constructed. Our approach for solving the constructed bicriteria partitioning problem consists of two phases. In the first phase, based on the covering’s matrix, we generate a matrix, the columns of which allow us to find all possible partitionings of the HADCs with the service centers. Some constraints are also taken into consideration while generating the matrix. In the second phase, based on the matrix and using our exact algorithm, we find the partitionings -allocations of the HADCs to the centers- which correspond to the Pareto-optimal solutions. For an illustration of the obtained results, a numerical example is given for the facility location-selection problem. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=emergency%20MAGDM" title="emergency MAGDM">emergency MAGDM</a>, <a href="https://publications.waset.org/abstracts/search?q=q-rung%20orthopair%20fuzzy%20sets" title=" q-rung orthopair fuzzy sets"> q-rung orthopair fuzzy sets</a>, <a href="https://publications.waset.org/abstracts/search?q=evidence%20theory" title=" evidence theory"> evidence theory</a>, <a href="https://publications.waset.org/abstracts/search?q=HADC" title=" HADC"> HADC</a>, <a href="https://publications.waset.org/abstracts/search?q=facility%20location%20problem" title=" facility location problem"> facility location problem</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-objective%20combinatorial%20optimization%20problem" title=" multi-objective combinatorial optimization problem"> multi-objective combinatorial optimization problem</a>, <a href="https://publications.waset.org/abstracts/search?q=Pareto-optimal%20solutions" title=" Pareto-optimal solutions"> Pareto-optimal solutions</a> </p> <a href="https://publications.waset.org/abstracts/164966/evidence-theory-based-emergency-multi-attribute-group-decision-making-application-in-facility-location-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/164966.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">92</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">1</span> Fuzzy Multi-Objective Approach for Emergency Location Transportation Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bidzina%20Matsaberidze">Bidzina Matsaberidze</a>, <a href="https://publications.waset.org/abstracts/search?q=Anna%20Sikharulidze"> Anna Sikharulidze</a>, <a href="https://publications.waset.org/abstracts/search?q=Gia%20Sirbiladze"> Gia Sirbiladze</a>, <a href="https://publications.waset.org/abstracts/search?q=Bezhan%20Ghvaberidze"> Bezhan Ghvaberidze</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In the modern world emergency management decision support systems are actively used by state organizations, which are interested in extreme and abnormal processes and provide optimal and safe management of supply needed for the civil and military facilities in geographical areas, affected by disasters, earthquakes, fires and other accidents, weapons of mass destruction, terrorist attacks, etc. Obviously, these kinds of extreme events cause significant losses and damages to the infrastructure. In such cases, usage of intelligent support technologies is very important for quick and optimal location-transportation of emergency service in order to avoid new losses caused by these events. Timely servicing from emergency service centers to the affected disaster regions (response phase) is a key task of the emergency management system. Scientific research of this field takes the important place in decision-making problems. Our goal was to create an expert knowledge-based intelligent support system, which will serve as an assistant tool to provide optimal solutions for the above-mentioned problem. The inputs to the mathematical model of the system are objective data, as well as expert evaluations. The outputs of the system are solutions for Fuzzy Multi-Objective Emergency Location-Transportation Problem (FMOELTP) for disasters’ regions. The development and testing of the Intelligent Support System were done on the example of an experimental disaster region (for some geographical zone of Georgia) which was generated using a simulation modeling. Four objectives are considered in our model. The first objective is to minimize an expectation of total transportation duration of needed products. The second objective is to minimize the total selection unreliability index of opened humanitarian aid distribution centers (HADCs). The third objective minimizes the number of agents needed to operate the opened HADCs. The fourth objective minimizes the non-covered demand for all demand points. Possibility chance constraints and objective constraints were constructed based on objective-subjective data. The FMOELTP was constructed in a static and fuzzy environment since the decisions to be made are taken immediately after the disaster (during few hours) with the information available at that moment. It is assumed that the requests for products are estimated by homeland security organizations, or their experts, based upon their experience and their evaluation of the disaster’s seriousness. Estimated transportation times are considered to take into account routing access difficulty of the region and the infrastructure conditions. We propose an epsilon-constraint method for finding the exact solutions for the problem. It is proved that this approach generates the exact Pareto front of the multi-objective location-transportation problem addressed. Sometimes for large dimensions of the problem, the exact method requires long computing times. Thus, we propose an approximate method that imposes a number of stopping criteria on the exact method. For large dimensions of the FMOELTP the Estimation of Distribution Algorithm’s (EDA) approach is developed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=epsilon-constraint%20method" title="epsilon-constraint method">epsilon-constraint method</a>, <a href="https://publications.waset.org/abstracts/search?q=estimation%20of%20distribution%20algorithm" title=" estimation of distribution algorithm"> estimation of distribution algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20multi-objective%20combinatorial%20programming%20problem" title=" fuzzy multi-objective combinatorial programming problem"> fuzzy multi-objective combinatorial programming problem</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20multi-objective%20emergency%20location%2Ftransportation%20problem" title=" fuzzy multi-objective emergency location/transportation problem"> fuzzy multi-objective emergency location/transportation problem</a> </p> <a href="https://publications.waset.org/abstracts/59595/fuzzy-multi-objective-approach-for-emergency-location-transportation-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/59595.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">321</span> </span> </div> </div> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/WASET-16th-foundational-anniversary.pdf">WASET celebrates its 16th foundational 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Search results for: B. Matsaberidze