求解TSP 问题的离散粒子群优化算法

以旅行商问题为例,提出了一种离散粒子群优化算法,根据优化问题及离散量的特点,对粒子的位置、速度等量及其运算规则进行了重新定义,为抑制早熟停滞现象,为粒子和粒子群分别定义了个体多样性和微观多样性,算法中定义了排斥算子来保持粒子群的多样性,使用高效的学习算子来提高算法的局部求精能力,使算法在空间探索和局部求精间取得了很好的平衡,与领域中的其它典型算法进行了仿真比较,结果表明,离散粒子群优化算法具有很好的性能.

Discrete Particle Swarm Optimization Algorithm for TSP Problem

A discrete particle swarm optimization algorithm is designed to tackle the Traveling Salesman Problem.Based on the characteristics of the problem at hand and discrete variable,this paper redefines particle's position,velocity and their operation rules.In order to restrain premature stagnation,individual diversity of particle and micro-diversity of particle swarm are defined.A repulsion operator is designed to keep the diversity of particle swarm,and an efficient learning operator is defined to improve the algorithm's intensification ability.Using those operators,the proposed algorithm can get good balance between exploration and exploitation.The simulation results comparing with typical algorithms from the literature show that it can produce good results.