基于多目标决策的多车场车辆调度干扰管理研究  

Research on Disruption Management of Multi-depot V ehicle Scheduling Based on Multi-objective Decision

作　　者：曹庆奎[1,2] 高亚伟 任向阳 袁雯慧[1] Cao Qingkui;Gao Yawei;Ren Xiangyang;Yuan Wenhui(Hebei University of Engineering,Handan 056038,China;Langfang Normal University,Langfang 065000,China)

机构地区：[1]河北工程大学,河北邯郸056038 [2]廊坊师范学院,河北廊坊065000

出　　处：《廊坊师范学院学报（自然科学版）》2021年第1期5-11,共7页Journal of Langfang Normal University(Natural Science Edition)

基　　金：国家自然科学基金项目(61375003);河北省社会科学基金项目(HB17GL022);河北省高等学校人文社会科学研究项目(SD181012)。

摘　　要：针对客户配送地址产生变动而导致初始运输方案难以顺利实施这一难题,考虑客户、物流运营商和配送人员三个行为主体的利益,以客户不满意度、运输费用和路线偏离最小为目标,建立多车场环境下多目标干扰管理数学模型。对目标函数进行规范化处理,将多目标问题简化为单目标问题。对遗传算法进行改进,引入迭代交换过程和自适应交叉变异算子求解干扰管理模型。通过MATLAB软件进行仿真,仿真结果与重调度法进行对比。结果表明,文中方法与现有的重调度法相比可以更好地平衡各方利益,得出扰动较小的调整方案。The initial distribution plan is difficult to implement due to changes in the customer distribution address.Aim-ing at this difficulty,this paper considers the interests of three parties:customers,logistics operators and distribution person-nel,aiming at customer dissatisfaction,transportation cost and path deviation minimization,a multi-objective disruption management model in a multi-depot environment is constructed.Normalize the objective function and transform the multi-objective problem into a single objective problem.To optimize the disruption management model,the genetic algo-rithm is improved by introducing iterated swap procedure and adaptive crossover mutation operator.After simulation by MATLAB software,the simulation results are compared with the rescheduling method.The results show that,compared with the existing rescheduling method,the method in this paper can balance the interests of all parties better and obtain a less disturbing adjustment scheme.

关 键 词：多目标 多车场 干扰管理 遗传算法 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]