Abstract: To compare the impact of remanufacturing subsidy and carbon tax on the optimization of closed-loop supply chain networks,a multi-objective scenario-fuzzy optimization model under different policies with the optimization objectives of minimizing economic cost,minimizing carbon emission and maximizing social benefit were developed.Fuzzy triangular numbers and scenario optimization handled the fuzzy and stochastic parameters,and the social benefit objective covered both customer needs and regional development.Then a goal attainment method suitable for integer programming was designed to solve the model.Based on the analysis of numerical examples,implementing remanufacturing subsidies and carbon tax could significantly reduce the carbon emissions from enterprise operations.The mechanisms of remanufacturing subsidy and carbon tax were similar,and both could affect the remanufacturing scale of enterprises and then promote emissions reduction and improve social benefits.In addition,to maximize the utility of the policies,it was necessary to consider the marginal benefit of subsidies and the cost pressure on enterprises.

Key words: remanufacturing subsidy, carbon tax, closed-loop supply chain, scenario-fuzzy optimization, goal attainment method

摘要： 为对比再制造补贴和碳税政策对闭环供应链网络优化的影响,以经济成本最小、碳排放量最低、社会效益最大为优化目标,构建不同政策下的多目标情景—模糊优化模型,分别用多情景优化和三角模糊数处理参数的不确定性,并基于顾客需求和地区发展的双维度评价指标构建社会效益目标函数,然后设计适用于整数规划的多目标到达算法对模型进行求解。通过算例证明,再制造补贴、碳税政策均能显著降低企业运营过程中的碳排放量;两项政策的作用机制相似,两者均可通过调控实施力度影响企业的再制造规模,进而在促进减排的同时提高社会效益;为了实现政策效用最大化,在实施再制造补贴和碳税政策时,需要考虑补贴的边际效益及企业承受的成本压力。

关键词: 再制造补贴, 碳税, 闭环供应链, 情景—模糊优化, 多目标到达算法