基于遗传算法的闭环物流网络随机规划模型  

Stochastic programming model of closed loop logistics network based on genetic algorithm

作　　者：李伯棠 赵刚[1] 葛颖恩[1] LI Botang ZHAO Gang GE Ying＇en(College of Transport ＆ Communications, Shanghai Maritime University, Shanghai 201306, China)

机构地区：[1]上海海事大学交通运输学院,上海201306

出　　处：《计算机集成制造系统》2017年第9期2003-2011,共9页Computer Integrated Manufacturing Systems

基　　金：国家自然科学基金资助项目(71431003);上海海事大学研究生创新基金资助项目(2016ycx066)~~

摘　　要：为解决不确定环境下的闭环物流网络设计问题,在消费者需求为随机量的情况下,考虑设施选址和节点间运输路线的决策,采用机会约束规划方法,以物流成本最小化为目标,建立一个闭环物流网络随机规划模型。根据问题的特点,以MATLAB为平台,编写了一个基于优先级编码的遗传算法代码,分别利用遗传算法和CPLEX对若干算例的求解结果进行了对比分析,验证了所提算法的可行性,并就需求变化进行了分析,结果表明随机规划模型的决策具有合理性和适用性。To solve the problem of closed-loop logistics network design under uncertain environment,the decision of facility location and transport route in the network was considered to establish a stochastic programming model of closed loop logistics network with chance constrained programming method in the case that consumer demand was random quantity,which took the minimum cost of logistics as the objective.According to the characteristics of the problem,a code based on priority coding genetic algorithm wrote in MATLAB.By using the genetic algorithm and CPLEX,the results of several numerical examples were compared and analyzed.The result verified the feasibility of the proposed genetic algorithm,and the analysis included the variation of demand showed that the decision of stochastic programming model was reasonable and applicable.

关 键 词：遗传算法 随机规划 闭环物流 网络规划 

分 类 号：F224[经济管理—国民经济]