模糊环境下的多目标非满载车辆调度问题  

Multi-objective Non-full Loaded Vehicle Scheduling Problemin Fuzzy Environment

作　　者：卢冰原[1] 何力[1] 贾兆红[2] 

机构地区：[1]南京工程学院经济管理学院,江苏南京211167 [2]安徽大学智能计算与信号处理教育部重点实验室,安徽合肥230039

出　　处：《公路交通科技》2011年第8期147-153,共7页Journal of Highway and Transportation Research and Development

基　　金：教育部人文社会科学研究青年基金项目(10YJC630165);江苏省教育厅高校哲学社会科学基金项目(09SJD630036)

摘　　要：针对现实物流配送过程中存在的时间参数模糊化问题,采用梯形模糊数表征时间参数,给出了一种具有模糊时间窗和模糊配送时间,以最小化配送车辆数、提前/滞后惩罚以及配送里程为目标的多目标非满载车辆调度问题模型。在问题求解方面,针对基本粒子群算法容易陷入局部最优的问题,引入利用混沌局部搜索策略,给出了一种基于混沌优化技术的混合粒子群算法。该求解算法的可行性和有效性最后通过仿真试验进行了验证。For solving the problem correlated with fuzzy temporal parameter in real logistics distribution,the trapezoidal fuzzy number was used to denote temporal parameter,based on which,a multi-objective non-full loaded vehicle scheduling problem（VSP） model for minimized vehicle number,earliness/tardiness penalties and delivery mileage which has fuzzy time window and fuzzy travel time was introduced at first.Aimed at the problem of easily getting into the local optimum of basic particle swarm optimization（PSO） algorithm,the chaotic local search policy was introduced,and a hybrid PSO algorithm based on chaotic optimization technology was proposed for the fuzzy multi-objective VSP problem above.At last,through the analysis of the simulating experiment results,the feasibility and efficiency of the algorithm were approved.

关 键 词：运输经济 调度优化 混合粒子群算法 车辆调度问题 模糊环境 

分 类 号：F540[经济管理—产业经济]