A memetic algorithm for the capacitated location-routing problem

dc.contributor.authorLaila Kechmane
dc.contributor.authorBenayad Nsiri
dc.contributor.authorAzeddine Baalal
dc.date.accessioned2019-06-02T09:26:49Z
dc.date.available2019-06-02T09:26:49Z
dc.date.issued2016-06-01
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.urihttp://e-biblio.univ-mosta.dz/handle/123456789/10553
dc.publisherInternational Journal of Advanced Computer Science and Applicationsen_US
dc.subjecthybrid genetic algorithmen_US
dc.subjectcapacitated locationrouting problemen_US
dc.subjectlocationen_US
dc.subjectassigningen_US
dc.subjectvehicle routingen_US
dc.titleA memetic algorithm for the capacitated location-routing problemen_US
dc.typeArticleen_US

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
3.pdf
Size:
851.64 KB
Format:
Adobe Portable Document Format
Description:

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description: