solving the capacitated vehicle routing problem based on improved ant-clustering algorithm

solving the capacitated vehicle routing problem based on improved ant-clustering algorithm

;Zhang Jiashan;Lin Xiaoqun;Jun Yi;Li Qiang
acta botânica brasílica 2015 Vol. 22 pp. 03022-
137
jiashan2015matecsolving

Abstract

The capacitated vehicle routing problems (CVRP) are NP-hard. Most approaches can solve small-scale case studies to optimality. Furthermore, they are time-consuming. To overcome the limitation, this paper presents a novel three-phase heuristic approach for the capacitated vehicle routing problem. The first phase aims to identify sets of cost-effective feasible clusters through an improved ant-clustering algorithm, in which the adaptive strategy is adopted. The second phase assigns clusters to vehicles and sequences them on each tour. The third phase orders nodes within clusters for every tour and genetic algorithm is used to order nodes within clusters. The simulation indicates the algorithm attains high quality results in a short time.

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ID: 209022
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0x95644003c57E6F55A65596E3D9Eac6813e3566dA
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209022
Unique Identifier:
10.1051/matecconf/20152203022
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