面向空间分布式小批量物流供需的多任务集成调度  

Integrated multi-task scheduling for spatially distributed small-batch logistics

作　　者：周林[1] 王旭[1,2] 林云[1,2] 景熠[3] 

机构地区：[1]重庆大学机械传动国家重点实验室,重庆400030 [2]重庆大学现代物流重庆市重点实验室,重庆400030 [3]重庆理工大学管理学院,重庆400054

出　　处：《计算机集成制造系统》2016年第3期822-832,共11页Computer Integrated Manufacturing Systems

基　　金：国家科技支撑计划资助项目(2015BAH46F01;2015BAF05B03);重庆市科技攻关计划资助项目(CSTC 2014yykfA40006;2015yykfC60002);中央高校基本科研业务费资助项目(CDJZR 14110001;13110048;106112015CDJSK02JD05);高等学校博士学科点专项科研基金资助项目(20130191110045);重庆理工大学青年科研项目星火支持计划(2014XH24)~~

摘　　要：针对供需呈空间分布的多个小批量物流服务需求,研究了面向多起始地—多目的地的多任务集成调度问题。基于分布式物流任务多路径与多集并的特点,设计了多任务物流服务网络图,综合考虑集并产生的费用折扣、等待成本与等待时间,从系统角度权衡任务个体与多任务整体利益,构建了以物流成本与延迟惩罚成本之和最小为目标的数学模型。针对模型求解过程中存在的变长度路径选择、多级集并、资源能力冲突等特点,设计了基于优先权的遗传算法对模型进行求解,并构造自适应变长度交叉与双变异机制增强求解效率。结合算例验证了模型和算法的有效性。To meet the demands of multiple small-batch logistics in spatially distributed,a multi-task scheduling problem oriented to multi-origin and multi-destination was researched.Based on multi-path and multi-consolidation characteristics of distributed logistic tasks,the multi-task logistics service network diagram was designed.For purpose of synthetically balancing the interests between overall multi-task and individual tasks,a mathematical model was proposed to minimize the sum of logistics and penalty cost by considering cost discount,waiting cost and waiting time caused by consolidation.In view of variable length path selection,multi-stage consolidation and resources capability confliction in the process of solving,the genetic algorithm based on priority was designed,and the adaptive variable length chromosome crossover and double mutation mechanisms were constructed to improve the efficiency.The effectiveness of proposed model and algorithm was verified by case study.

关 键 词：多任务集成调度 多级集并 小批量物流 遗传算法 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]