计算机应用研究2012，Vol.29Issue(3)：869-872,876,5.DOI:10.3969/j.issn.1001-3695.2012.03.019
求解VRPTW问题的不确定性目标偏好蚁群算法
Uncertain linguistic information objectives preference VRPTW of ant colony algorithm
摘要
Abstract
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 transferred 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.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Key words
vehicle routing problem( VRP) / time window/ objectives preference/ uncertain linguistic information/ ant colony algorithm/ max-min ant system ( MM AS)分类
信息技术与安全科学引用本文复制引用
李世威,王建强,曾俊伟..求解VRPTW问题的不确定性目标偏好蚁群算法[J].计算机应用研究,2012,29(3):869-872,876,5.基金项目
国家社科基金资助项目(11CJY067) （11CJY067）
甘肃省自然科学基金资助项目(096PJZA088) （096PJZA088）
