改进的粒子群优化算法在随机需求车辆路径问题中的应用

Advanced Particle Swarm Optimization for the Vehicle Routing Problem with Stochastic Demands

设计了一种求解随机需求车辆路径问题的改进的粒子群优化(PSO)算法.在算法后期将变异算子引入PSO算法,克服了基本PSO算法易陷入局部最优的缺点.数值模拟结果表明改进的PSO算法提高了全局搜索能力,求解效果优于基本PSO算法和遗传算法.

This paper studies the vehicle routing problem with stochastic demands（VRPSD）, and devises an advanced PSO to solve this problem. By adding the mutation operator to the PSO algorithm in the later phase, the advanced PSO algorithm overcome the basic PSO＇s shortcoming of easily plunging into the local optimization. Experimental results indicate that the advanced PSO algorithm can improve the global convergence ability and is superior to basic PSO algorithm and genetic algorithm.