期刊
SOFT COMPUTING
卷 26, 期 17, 页码 8745-8756出版社
SPRINGER
DOI: 10.1007/s00500-022-07198-2
关键词
Ant colony optimization; Capacitated vehicle routing problem; Discrete combinatorial optimization problem; Evolutionary algorithm
资金
- National Natural Science Foundation of China [51875466, 52175251]
This paper introduces a new ant colony optimization algorithm called dynamic space reduction ant colony optimization (DSRACO) to solve the capacitated vehicle routing problem. The experimental results show that DSRACO can solve this problem with satisfactory results.
As a typical meta-heuristic algorithm, ant colony optimization (ACO) has achieved good results in solving discrete combinatorial optimization problems. However, it suffers from poor solutions and the drawback of easily being trapped in local optima. This paper presents a new type of ACO called dynamic space reduction ant colony optimization (DSRACO) to solve the capacitated vehicle routing problem, which is a typical nondeterministic polynomial-hard optimization problem. In DSRACO, ACO is integrated with a unique dynamic space reduction method, an elite enhanced mechanism, and large-scale neighborhood search methods to improve the quality of the solution. The performance of DSRACO is evaluated using 73 well-known benchmark instances in comparison with ACO and three other cutting-edge algorithms. The experimental results show that DSRACO can solve CVRP with a satisfactory result.
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