摘要
为优化具有模糊预约时间的车辆路径问题,应用模糊事件给出了车队服务满意度的一个新的度量方法和求最大满意度的计算方法。建立了多目标数学规划模型,并提出多目标禁忌搜索算法求解Pareto最优解。采用随机车辆配载方法生成初始解放入候选解池中,提出插入可行邻域和2-Opt可行邻域进行邻域搜索。对池中的Pareto解进行并行的禁忌搜索得到局部Pareto解再注入池中,最后求得一组Pareto解。通过Solomon的bench-mark算例,与非支配排序遗传算法Ⅱ进行对比实验,说明了所提算法的优越性。
To optimize vehicle routing problem with fuzzy due-time,a new method to measure and calculate the maximum satisfaction was proposed by using fuzzy event.A multi-objective mathematical programming model was designed,and a multi-objective tabu search algorithm to solve Pareto optimal solutions was proposed.Initial solutions were generated by random vehicle loading method,which were put into candidate solution pool.And the neighborhood search was carried out based on insertion and 2-Opt feasible neighborhoods.Each Pareto solution in the pool was optimized by parallel tabu search.Compared to the Nondominated Sorting Genetic Algorithm II（NSGA-Ⅱ）,the effectiveness of the proposed method was verified by computational experiments on Solomon benchmarks.
出处
《计算机集成制造系统》
EI
CSCD
北大核心
2011年第4期858-866,共9页
Computer Integrated Manufacturing Systems
基金
新世纪优秀人才支持计划资助项目(NCET-06-0236)
高等学校博士学科点专项科研基金资助项目(20100032110034)~~
