摘要
针对粒子群算法解决多车场带时间窗车辆路径问题时产生不可行解较多的问题,设计了对不可行解根据个体极值进行调整的策略,优化不可行解的粒子群算法,并且引入变异算子,增强了粒子寻找最优解的能力.实验结果表明,该算法可以快速求得多车场带时间窗车辆路径问题的目前最优解,提高算法的精度,加快收敛速度,跳出局部最优.
There will be some infeasible solutions when solving multi-depot vehicle routing problem with time windows（ MDVRPTW） by the means of the particle swarm optimization（ PSO） algorithm. In this paper,aiming at this issue,the infeasible solutions are adjusted according to the individual extreme,the particle swarm algorithm is optimized,the mutation operator is introduced and the ability of finding optimal solutions for particles is enhanced. Experimental results show that this algorithm can quickly obtain current optimal solution for MDVRPTW,improve the accuracy of the algorithm,accelerate convergence,and jump out of local optimization.
出处
《兰州工业学院学报》
2015年第2期51-55,共5页
Journal of Lanzhou Institute of Technology
关键词
多车场带时间窗车辆路径问题
粒子群优化算法
不可行解调整
变异
Multi-Depot Vehicle Routing Problem with Time Windows（MDVRPTW）
particle swarm optimization（PSO） algorithm
infeasible solution adjustment
mutation operator
