摘要
车辆路径规划是物流配送导航系统中的关键环节,是实现物流配送路径引导的前提条件和车辆导航的技术保障.为解决物流配送车辆导航中的路径规划问题,文中建立了物流配送车辆导航路径规划(VND)遍历模型,设计了求解该模型的改进型粒子群算法,并对初始种群的产生方法及种群的进化策略进行改进,使原本不能直接用于求解VND模型的基本粒子群优化(PSO)算法,在求解VND问题上取得了很好的效果.通过简单算例验证模型和算法的结果表明,该算法具有快速的运算能力和较好的收敛性.
Vehicle routing planning is known as the key link in the logistics delivery vehicle navigation system as well as the precondition for the logistics delivery routing guidance and the technical support for vehicle navigation. In order to solve the routing planning problem, an ergodic model is established for Vehicle Routing Planning of Navigation in Logistics Distribution （VND）, and an improved particle swarm optimization algorithm is proposed to solve the model. Then, the generation method of the initial population and the evolutionary strategy of the population are improved to work out the PSO algorithm which ori ginally can not be directly used to solve the VND problem, thus achieving good results in solving the VND problem. ting capability and preferable convergence.
出处
《华南理工大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2011年第8期109-112,117,共5页
Journal of South China University of Technology(Natural Science Edition)
基金
国家自然科学基金资助项目(50978106)
关键词
配送车辆导航
路径规划
遍历模型
粒子群优化算法
种群进化
delivery vehicle population evolution navigation
routing planning
Case studies show that the algorithm is of fast compu- ergodic model
particle swarm optimization algorithm
