A memetic algorithm for the capacitated location-routing problem
| 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.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.identifier.uri | http://e-biblio.univ-mosta.dz/handle/123456789/10553 | |
| 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 |