摘要
在对随机需求信息条件下的车辆路径问题进行策略分析基础上,提出解决此类问题的改进蚁群算法。分析对比不同策略下用蚁群算法优化的结果。其中给出机会约束下决策者的风险喜好对最终目标的影响。通过模拟实际随机需求的方法评价先验路径的优劣。与其它计算方法在同等条件下的比较证明所设计算法的优越性。同时得出对于不同统计特性的随机需求策略的选择方式。
On the basis of analyzing strategy for solving vehicle routing problem with stochastic demands （VRPSD）, a modify ant colony optimize algorithm is proposed to solve the VRPSD. The characteristic of strategy and the result got from ant colony optimize algorithm are analyzed. The influence of the decisionmaker＇s preference on the final objective of the problem is discussed under the method of opportunity restriction. Using the real demands based on statistical simulation appraised the prior routing. Compared its performance with another heuristic designed for the same case. Experimental results show that the algorithm is feasible and valid for VRPSD. And the choice of strategy for the stochastic demands with different statistic is got.
出处
《计算机工程与设计》
CSCD
北大核心
2007年第1期138-141,148,共5页
Computer Engineering and Design
基金
国家教委留学归国人员基金项目(BAQQ24403001)
关键词
物流配送
蚁群算法
随机需求
车辆路径问题
启发式算法
distribution management
ant colony optimize algorithm
stochastic demands
vehicle routing problem
meta-heuristics
