Arşiv ve Dokümantasyon Merkezi
Dijital Arşivi

Heuristics for the probabilistic capacitated multi-facility weber problem

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dc.contributor Graduate Program in Industrial Engineering.
dc.contributor.advisor Altınel, İ. Kuban.
dc.contributor.author Durmaz, Engin.
dc.date.accessioned 2023-03-16T10:27:52Z
dc.date.available 2023-03-16T10:27:52Z
dc.date.issued 2007.
dc.identifier.other IE 2007 D87
dc.identifier.uri http://digitalarchive.boun.edu.tr/handle/123456789/13182
dc.description.abstract In this study, we consider the probabilistic capacitated multi-facilityWeber problem with general distance functions and probability density functions where customer locations are assumed to be random variables. The aim of the problem is to find supply points and allocations by minimizing the expected sum of demand weighted distances. Since customer locations are random, it is not always possible to obtain analytical expressions for expected distances between facilities and customers. First, we used general distance functions and probability distributions for our problem. Afterwards, we specialized the problem using two distance functions to examine different instances: Euclidean and rectilinear distances. For the Euclidean distance, we assume that customer locations follow symmetric bivariate normal and symmetric bivariate exponential probability distributions. In addition to these two probability distributions, symmetric bivariate uniform probability distribution is also assumed for the rectilinear distance. Solving this problem to optimality with known optimization techniques is very hard since the objective function of the problem is neither convex nor concave. In order to solve the problem, we have developed four heuristic methods. The first one is the probabilistic alternating location-allocation heuristic and the other three of them depend on discrete approximations. Furthermore, we have also developed three approximation methods for calculating the expected distances for different situations. These new approaches are implemented and computational results based on extensive experiments are also provided.
dc.format.extent 30cm.
dc.publisher Thesis (M.S.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2007.
dc.subject.lcsh Industrial location -- Mathematical models.
dc.subject.lcsh Heuristic.
dc.title Heuristics for the probabilistic capacitated multi-facility weber problem
dc.format.pages xiii, 127 leaves;


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