一种新的进化粒子群算法及其在TSP中的应用

Novel evolutionary Particle Swarm Optimization for Traveling Salesman Problem

基于协同进化的思想,针对离散组合优化的NP难问题,提出一种新的混合粒子群进化算法。该算法采用了有效的编码方式;定义了两个粒子间的位置加法操作以实现个体之间的信息交换;引入变异算子保持种群多样性。该算法应用于TSP优化计算,能用较小的计算代价得到比传统方法更满意的解,实验结果表明该算法是有效的。

Inspired from the co-evolutionary,this paper proposes a new hybrid particle swarm evolutionary algorithm for solving the Traveling Salesman Problem （TSP）,which is one of the most known NP hard problem.The algorithm adopts an effective code schema and defines a new addition operation of the particle＇s position in order to exchange information among the particles.A mutation operator is designed to keep the population＇s diversity.The experiments show that this algorithm has better convergence effectiveness.