A hybrid ant colony algorithm based on multiple strategies for the vehicle routing problem with time windows

被引:0
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作者
Hongguang Wu
Yuelin Gao
Wanting Wang
Ziyu Zhang
机构
[1] North Minzu University,School of Mathematics and Information Science
[2] North Minzu University,Ningxia Province Key Laboratory of Intelligent Information and Data Processing
[3] North Minzu University,Ningxia Province Cooperative Innovation Center of Scientific Computing and Intelligent in Formation Processing
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关键词
Vehicle routing problem; Ant colony algorithm; Mutation operation; Adaptive parameter; Practical application;
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学科分类号
摘要
In this paper, we propose a vehicle routing problem with time windows (TWVRP). In this problem, we consider a hard time constraint that the fleet can only serve customers within a specific time window. To solve this problem, a hybrid ant colony (HACO) algorithm is proposed based on ant colony algorithm and mutation operation. The HACO algorithm proposed has three innovations: the first is to update pheromones with a new method; the second is the introduction of adaptive parameters; and the third is to add the mutation operation. A famous Solomon instance is used to evaluate the performance of the proposed algorithm. Experimental results show that HACO algorithm is effective against solving the problem of vehicle routing with time windows. Besides, the proposed algorithm also has practical implications for vehicle routing problem and the results show that it is applicable and effective in practical problems.
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页码:2491 / 2508
页数:17
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