Solving the Capacitated Vehicle Routing Problem Based on Improved Ant-clustering Algorithm

Autor: Zhang Jiashan, Lin Xiaoqun, Jun Yi, Li Qiang
Jazyk: English<br />French
Rok vydání: 2015
Předmět:
Zdroj: MATEC Web of Conferences, Vol 22, p 03022 (2015)
Druh dokumentu: article
ISSN: 2261-236X
DOI: 10.1051/matecconf/20152203022
Popis: 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.
Databáze: Directory of Open Access Journals