一种改进的离散粒子群优化算法

针对旅行商问题，提出了一种改进的离散粒子群优化算法，根据优化问题及离散量的特点，对粒子的速度、速度的相关运算规则和粒子的运动方程进行了重新定义，为防止算法的早熟停滞现象，提出用扰动速度来增加粒子群的多样性，为提高算法的求精能力，设计了一种高效的近邻搜索算子来提高粒子的适应值，使算法在空间探索和局部精化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，该算法具有很好的性能．

An Improved Discrete Particle Swarm Optimization Algorithm

A new improved 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 velocity, the operation rules of velocity, and the moving equation of particle. In order to keep the algorithm from premature stagnation, disturbing velocity is used to increase the diversity of particle swarm. In order to improve the algorithm's intensification ability, a high performance local search operator is designed to improve the particle's fitness. Using those strategies, 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 better results.