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A memetic algorithm for the capacitated location-routing problem

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dc.contributor.author Laila Kechmane
dc.contributor.author Benayad Nsiri
dc.contributor.author Azeddine Baalal
dc.date.accessioned 2019-06-02T09:26:49Z
dc.date.available 2019-06-02T09:26:49Z
dc.date.issued 2016-06-01
dc.identifier.uri http://e-biblio.univ-mosta.dz/handle/123456789/10553
dc.description.abstract —In this paper, a hybrid genetic algorithm is proposed to solve a Capacitated Location-Routing Problem. The objective is to minimize the total cost of the distribution in a network composed of depots and customers, both depots and vehicles have limited capacities, each depot has a homogenous vehicle fleet and customers’ demands are known and must be satisfied. Solving this problem involves making strategic decisions such as the location of depots, as well as tactical and operational decisions which include assigning customers to the opened depots and organization of the vehicle routing. To evaluate the performance of the proposed algorithm, its results are compared to those obtained by a greedy randomized adaptive search procedure, computational results shows that the algorithm gave good quality solutions. en_US
dc.publisher International Journal of Advanced Computer Science and Applications en_US
dc.subject hybrid genetic algorithm en_US
dc.subject capacitated locationrouting problem en_US
dc.subject location en_US
dc.subject assigning en_US
dc.subject vehicle routing en_US
dc.title A memetic algorithm for the capacitated location-routing problem en_US
dc.type Article en_US


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