An enhanced ant colony optimization (EACO) applied to capacitated vehicle routing problem

Authors:
Chou-Yuan Lee;Zne-Jung Lee;Shih-Wei Lin;Kuo-Ching Ying
Affiliations:
Dept. of Information Management, Lan Yang Institute of Technology, I Lan, Taiwan 261;Department of Information Management, Huafan University, Taipei County, Taiwan 22301;Department of Information Management, Chang Gung University, Tao-Yuan, Taiwan;Department of Industrial Engineering and Management Information, Huafan University, Taipei County, Taiwan 22301
Venue:
Applied Intelligence
Year:
2010

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Abstract

In this paper, an enhanced ant colony optimization (EACO) is proposed for capacitated vehicle routing problem. The capacitated vehicle routing problem is to service customers with known demands by a homogeneous fleet of fixed capacity vehicles starting from a depot. It plays a major role in the field of logistics and belongs to NP-hard problems. Therefore, it is difficult to solve the capacitated vehicle routing problem directly when solutions increase exponentially with the number of serviced customers.The framework of this paper is to develop an enhanced ant colony optimization for the capacitated vehicle routing problem. It takes the advantages of simulated annealing and ant colony optimization for solving the capacitated vehicle routing problem. In the proposed algorithm, simulated annealing provides a good initial solution for ant colony optimization. Furthermore, an information gain based ant colony optimization is used to ameliorate the search performance. Computational results show that the proposed algorithm is superior to original ant colony optimization and simulated annealing separately reported on fourteen small-scale instances and twenty large-scale instances.