求解旅行商问题的离散型贝壳漫步优化算法*

提出基于离散型贝壳漫步优化算法(DMWO)的旅行商问题(TSP)求解算法.在DMWO的计算框架下构造TSP相应的评估函数及个体差异度量算子.针对离散型算法整体调整容易破坏已形成的较优路径问题,采用简单的2-opt算子进行局部调整,增强算法在求解TSP时的局部搜索能力.实验中采用多组不同规模的标准TSPLIB数据,对比同样采用2-opt算子的萤火虫优化算法和蚁群优化算法,DMWO在稳定性、解的准确性及所需的迭代次数等方面具有更好的性能.

Discrete Mussels Wandering Optimization Algorithm for Solving Traveling Salesman Problem

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.