考虑负外部性的动力电池可持续逆向物流网络优化

Optimization of power battery sustainable reverse logistics network con sidering negative externalities

随着新能源汽车动力电池退役潮的到来,相关逆向物流设施的规模也在不断扩张,动力电池回收拆解中心及其附属活动带来的环境及社会负外部性也日益突出,亟须从可持续角度对退役动力电池逆向物流网络进行优化。考虑回收数量和再循环比例的不确定性,引入风险接受度函数(risk acceptance function,RAF),本文以成本最小化、碳排放量最小化和风险接受度最大化为目标构建多目标混合整数规划模型,通过大规模算例验证了模型与算法的有效性,并对参数进行敏感性分析。与单目标优化模型相比,多目标决策模型能有效促进经济、环境与社会三者协调发展;回收量置信水平的增大可引起成本、碳排放量的持续增加以及风险接受度的持续降低;再循环比例及其置信水平的增大可使得成本与碳排放量呈递减变化,以及风险接受度呈递增变化。

With the advent of the retirement tide of power batteries of new energy vehicles,the scale of related reverse logistics facilities is expanding,and the negative environmental and social externalities brought by power battery recycling and dismantling centers and their affiliated activities are also becom-ing increasingly prominent.It is urgent to optimize the retired power battery reverse logistics network from the perspective of sustainability.Considering the uncertainty of recovery quantity and recycling ratio,risk acceptance function(RAF)was introduced to construct a multi-objective mixed integer pro-gramming model with the objectives of minimizing cost,minimizing carbon emission and maximizing risk acceptance.The effectiveness of the model and the algorithm is verified by a large-scale numerical example,and the sensitivity of the parameters is analyzed.Compared with the single objective optimiza-tion model,the multi-objective decision-making model can effectively promote the coordinated develop-ment of economy,environment and society.The increase of recovery confidence level can lead to the con-tinuous increase of cost,carbon emission and the continuous decrease of risk acceptance.The increase of the recycling ratio and its confidence level can lead to a decreasing change in cost and carbon emis-sions,and an increasing change in risk acceptance.