摘要
通过分析多目标的、有时间窗的车辆路径问题,对各个目标进行多属性不确定性语言评判,结合相关专家的综合意见以及决策者自身对专家意见的偏好,将决策者对目标属性的离散意见转换为对各目标的综合意见;通过定义一种综合排序指标来确定决策者对各目标的偏好权重,依据目标权重和各目标函数的规范化处理值,构建评价有时间窗的车辆路径问题的多目标偏好的综合适应度函数,将多目标问题转换为单目标问题,进而采用最大—最小蚂蚁系统算法对该问题进行求解;最后通过一个算例来说明该算法的有效性。
By analyzing the multi-objectives vehicle routing problem with time window, it uncertain evaluated multi-attributes of each objective, combined the comprehensive views of the relevant decision-makers, and transferred discrete levels of objective＇ s attributes to integrated levels. After that, it defined an integrated index to determine each objective sorting weight, and determined the multi-objective integrated fitness function of vehicle routing problem with time window base on objective＇ s weights and standardized objective function value, it transfered multi-objectives problem into single objective problem. Then it used max-min ant system algorithm to solve the problem. Finally, it used a case to illustrate the algorithm＇ s effectiveness.
出处
《计算机应用研究》
CSCD
北大核心
2012年第3期869-872,876,共5页
Application Research of Computers
基金
国家社科基金资助项目(11CJY067)
甘肃省自然科学基金资助项目(096RJZA088)
关键词
车辆路径问题
时间窗
目标偏好
不确定性语言信息
蚁群算法
最大—最小蚂蚁系统
vehicle routing problem（VRP）
time window
objectives preference
uncertain linguistic information
ant colony algorithm
max-min ant system（MMAS）
