Abstract: To introduce the concept of sustainable development into the power battery recycling management,a multi-objective mathematical model considering the dual channel recycling mode of power battery was proposed for designing a sustainable reverse logistics network considering the balanced development of economy,environment and society to the recycling and treatment of waste power battery.In addition,the impact of price competition and recycling publicity was also considered.Meanwhile,a method of standard integration was used in dealing with multiple objective functions,and an improved hybrid co-evolution genetic algorithm was used to solve the model.The validity of the model and algorithm,and the sensitivity of each parameter were analyzed through the analysis of a calculation example.The research results showed that the multi-objective decision-making model could effectively promote the coordinated development of economic benefit,environmental benefit and social benefit compared with the single-objective optimization model;the competition of recycling channels would cause change in the choice of manufacturers,and the continuous increase of competitive intensity would lead to the decline of the objectives;the increasing of the uncertainty level of confidence could cause the continuous increase of the sustainable objectives,and the increasing of the confidence level of the sellers would cause the decrease of the number of alternative manufacturers.

Key words: power battery recycling, sustainable reverse logistics, dual-channel recycling mode, network optimization, hybrid co-evolution genetic algorithm

摘要： 为将可持续发展理念纳入动力电池回收管理工作中,构建一个考虑动力电池双渠道回收模式的多目标数学模型,为废旧动力电池回收处理设计考虑经济、环境和社会三者平衡发展的可持续逆向物流网络。模型考虑了价格竞争和回收宣传的影响,同时,将多目标函数进行标准整合,设计了改进混合协同进化遗传算法对模型求解。最后通过算例分析了模型及算法的有效性,并对参数进行敏感性分析。研究结果表明:多目标决策模型与单目标优化模型相比,能有效促进经济效益、环境效益和社会效益的协调发展;回收渠道的竞争行为会引起厂商的选择变化,且竞争强度的持续增加将导致各指标的下降;不确定置信度水平的增大可引起可持续目标的持续增加,销售商置信水平的增加会引起备选厂商选择数量的减小。

关键词: 动力电池回收, 可持续逆向物流, 双渠道回收模式, 网络优化, 混合协同进化遗传算法