求解TSP的变邻域蝙蝠算法

Variable neighborhood bat algorithm for TSP

针对现有蝙蝠算法易早熟、收敛不精等问题,提出一种变邻域蝙蝠算法。通过结合三种变邻域策略,提升算法局部搜索能力,同时加入惯性权重,均衡算法前期的全局搜索能力和后期的局部搜索能力。结果表明提出的变邻域蝙蝠算法能够有效地解决TSP问题,且效果比其他传统算法更优。

Aiming at the problems of premature convergence and poor convergence of existing bat algorithms,a variable neighborhood bat algorithm is proposed.By combining three variable neighborhood strategies,the local search ability of the algorithm is improved,and the inertia weight is added to balance the global search ability in the early stage and the local search ability in the later stage.The results show that the proposed variable neighborhood bat algorithm can effectively solve the TSP problem,and the effect is better than other traditional algorithms.