不确定环境下报废汽车逆向物流网络鲁棒优化  

Robust Optimization of End-of-Life Vehicles for Reverse Logistic Network with Uncertainty

作　　者：抄敏敏 王宁[1] CHAO Minmin;WANG Ning(School of Automobile,Chang′an University,Xi′an,Shaanxi 710064,China)

机构地区：[1]长安大学汽车学院,陕西西安710064

出　　处：《工业工程与管理》2022年第4期85-96,共12页Industrial Engineering and Management

基　　金：陕西省自然科学基金(2019JM-495,2020JQ-399);榆林市科技计划项目(CXY-2020-025)。

摘　　要：针对不确定环境下报废汽车逆向物流网络规划成本高的现实问题,以汽车生产商为主体构建了一个6层的报废汽车逆向物流网络。从经济、环境和社会3个角度出发,建立了多目标混合整数线性规划模型,研究了如何确定回收点、处理点和再制造点的位置、数量、等级和容量,以及网络各节点间运输量的分配。同时考虑回收率、运输成本、处理成本和再制造成本不确定因素,建立了鲁棒优化模型,基于鲁棒优化理论将半定规划模型转化为线性的鲁棒对应模型,并通过6个不同规模的算例验证了模型的准确性。研究结果表明:鲁棒模型在不确定环境下优于确定模型,处理成本和再制造成本对网络成本影响最大,为汽车生产商构建网络提供决策参考。In view of the high cost of building the reverse logistics network of end-of-life vehicles in the uncertain environment,a six-layer reverse logistics network of end-of-life vehicles was constructed by the vehicle manufacturer.From the three perspectives of economy,environment and society,a multi-objective mixed-integer linear programming model was established to study how to determine the location,quantity,grade and capacity of recovery points,processing points and remanufacturing points,as well as the distribution of traffic between nodes of the network.In addition,considering the uncertain factors of recovery rate,transportation cost,processing cost and remanufacturing cost,a robust optimization model was developed.The accuracy of the model was verified by six different scale examples.The results show that the robust model is better than the deterministic model in the uncertain environment,and the processing and remanufacturing costs have the greatest impact on the network cost,which provides a decision-making reference for the vehicle manufacturers to build the network.

关 键 词：报废汽车 逆向物流网络 不确定 鲁棒优化 

分 类 号：F272[经济管理—企业管理]