激励相容理论下再制造绿色供应链网络模糊优化  

Fuzzy optimization of remanufacturing green supplychain networkunder incentive compatibility theory

作　　者：王振 叶春明[1] 郭健全[1] Wang Zhen;Ye Chunming;Guo Jianquan(School of Management,University of Shanghai for Science&Technology,Shanghai 200093,China)

机构地区：[1]上海理工大学管理学院,上海200093

出　　处：《计算机应用研究》2025年第1期242-249,共8页Application Research of Computers

基　　金：上海市哲学社会科学规划项目(2022BGL010);国家自然科学基金资助项目(71840003)。

摘　　要：为探讨政府干预在供应链回收网络中的作用,基于激励相容理论,建立以最低总成本、最少碳排放和最大大数据投资回报为目标的多周期多目标优化模型,采用多目标三角模糊数和改进混合算法进行求解。结果表明:改进混合算法在处理回收网络多周期多目标方面具有较强的求解能力;政府政策能弥补制造业减排能力弱的问题。结论如下:制造业企业运用人工智能技术回收再制造能够提升竞争力;政府引导能够帮助企业实现产业升级。To investigate the role of government intervention in supply chain recovery networks,this paper proposed a multi-period and multi-objective optimization model based on incentive compatibility theory,aiming at the lowest total cost,minimal carbon emissions,and maximum big data investment returns.The method used multi-objective triangular fuzzy numbers and an improved hybrid algorithm to solve the model.The results show that the improved hybrid algorithm has strong solving capabilities for multi-period,multi-objective recovery networks,and government policies can compensate for the weak emission reduction capabilities of the manufacturing industry.The conclusions are as follows:the use of artificial intelligence technology in recovery and remanufacturing enhances the competitiveness of manufacturing enterprises,government guidance helps enterprises achieve industrial upgrading.

关 键 词：不确定环境 激励相容理论 模糊机会约束规划 多目标多周期供应链 改进混合算法 政府干预 

分 类 号：F272[经济管理—企业管理]