求解旅行商问题的离散型贝壳漫步优化算法<sup>*</sup>

doi:10.16451/j.cnki.issn1003-6059.201607009

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Abstract A discrete mussels wandering optimization (DMWO) algorithm is designed for solving the traveling salesman problem (TSP). An evaluation function and a measure operator indicating differences among mussels are given within DWMO framework. To overcome the defect caused by the overall discrete routine adjustment, a local routine adjustment strategy based on 2-opt is adopted to enhance the searching ability of the algorithm. The experiment is conducted on several standard TSPLIB testing data of different sizes. Compared with discrete glowworm swarm optimization and ant colony optimization adopting 2-opt, the results show the competitive performance of the proposed algorithm in terms of solution consistency, accuracy and the number of iterations.

Key words： Traveling Salesman Problem (TSP) Discrete Mussels Wandering Optimization (DMWO) 2-opt

Received: 01 June 2015

ZTFLH:

TP 391

About author:: HAN Wei(Corresponding author), born in 1975, Ph.D., associate professor. His research interests include artificial intelligence.ZHANG Zicheng, born in 1991, master student. His research interests include data mining and artificial intelligence.

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Cite this article:

HAN Wei,ZHANG Zicheng. Discrete Mussels Wandering Optimization Algorithm for Solving Traveling Salesman Problem[J]. , 2016, 29(7): 650-657.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.201607009 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2016/V29/I7/650

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