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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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