摘要
在制订车辆行驶路径的过程中,需求的随机性增加了决策的复杂性和难度.在顾客需求不可分割,并且准确的需求量信息在车辆到达该顾客点时才能获知的假设下,研究了一种随机顾客和随机需求量的车辆路径问题(VRPSCD).首先提出了多回路策略,并分析了该策略的渐近性;为了找到高质量的预回路,设计了具有不同邻域结构的模拟退火算法.通过实验不仅验证了多回路策略的有效性,而且表明混合邻域结构模拟退火算法的优越性.
Stochastic demands enhance complexity and difficulty of decision-making in the process of vehicle routing. Assumed that exact demands of customers are obtained only after vehicle visit them, and can not be divided, a version of vehicle routing problem with stochastic customers and stochastic demands （VRPSCD） is introduced. Firstly, multi-tour policy is put forward, and its asymptotic property is analyzed. To find a superior prior tour, several simulated annealing algorithms with different neighborhood structures are designed. Experiments demonstrate validity of multi-tour policy, and show superiority of the simulated annealing with combined neighborhood.
出处
《系统工程理论与实践》
EI
CSCD
北大核心
2007年第2期167-171,共5页
Systems Engineering-Theory & Practice
基金
国家自然科学基金(70673016)
中国博士后科学基金(20060390225)
关键词
车辆路径问题
随机需求
预优化
多回路策略
模拟退火算法
vehicle routing problem
stochastic demand
prior optimization
multi-tour policy
simulated annealing
