动力电池逆向物流网络多目标设计:风险优化与求解分析  

Multi-objective design of electric vehicle battery reverse logistics network:risk optimization and solution analysis

作　　者：范志强 罗一帆 梁宁宁 李姗姗 FAN Zhiqiang;LUO Yifan;LIANG Ningning;LI Shanshan(School of Business Administration Research Center for Economics,Henan Polytechnic University,Jiaozuo 454003,China;School of Finance and Economics Administration,Henan Polytechnic University,Jiaozuo 454003,China)

机构地区：[1]河南理工大学工商管理学院能源经济研究中心,河南焦作454003 [2]河南理工大学财经学院,河南焦作454003

出　　处：《重庆理工大学学报(自然科学)》2023年第11期333-342,共10页Journal of Chongqing University of Technology:Natural Science

基　　金：国家社会科学基金项目(23BGL058);河南省哲学社会科学规划项目(2022BJJ048);河南省高校基本科研业务费专项资金项目(SKJZD2020-01);河南理工大学青年骨干教师资助计划项目(2019XQC-21)。

摘　　要：在动力电池大量退役背景下,考虑风险、不确定性、多处理技术工艺等因素,以最小化风险与成本为目标,构建了动力电池逆向物流网络多目标规划模型。运用期望区间、期望值和模糊机会约束方法对模型进行确定性转化,通过优化搜索空间、构建边际变化率和新的转换函数对经典MW求解方法进行改进。实验结果表明:模型能够在有效控制风险的同时兼顾经济性,改进的MW方法在Pareto最优解数量、交互优化效率与求解时间方面明显优于MW方法,可为有限信息不确定环境下动力电池逆向物流网络风险控制决策提供理论与技术支持。As large quantities of power batteries go off the market,a multi-objective planning model of power battery reverse logistic network is built to minimize risks and costs with full consideration of risks,uncertainties and multi-processing techniques.Expected interval,expected value and fuzzy chance constraint methods are employed to transform the model deterministically.The classic MW solution method is improved by optimizing the search space,constructing marginal rates of change and new transformation function.Our experimental results show the model effectively controls the risk and achieves high economy.The improved MW method is markedly superior to the MW method in terms of the number of Pareto optimal solutions,interaction optimization efficiency and solution time.Thus,it provides the theoretical basis and technical support for risk control decision of power battery reverse logistic network in uncertain circumstances of limited information.

关 键 词：动力电池 风险优化 边际变化率 转换函数 交互优化效率 

分 类 号：F252[经济管理—国民经济]