考虑条件风险值的动力电池闭环供应链网络优化设计

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中图分类号：F253.4 文献标志码：A

Abstract： In order to explore the impact uncertainty in recycling quantity，dem quantity， their associated risks on the power battery closed-loop supply chain network structure，a conditional-risk-atvalue （CVaR）measurement method is adopted with the maximum prit as a goal，a mixed integer programming model under certain environments a two-stage stochastic programming model under riskneutral risk-averse situations are constructed，respectively.The scenario method is used to deal with parameter uncertainty， an improved genetic algorithm based on hybrid coding is proposed to solve models.The effectiveness the stochastic model the algorithm is verified through solving examples. The results show that：under a certain environment，prits increase as the recycling utilization rate increases；in the risk-averse situation，the increase in the degree risk aversion reduces prits. Therefore，decision makers need to consider how much prit to sacrifice to deal with risks. Comparing the results three situations，it is found that considering the uncertainty parameters their adverse effects will reduce network prits change the network structure.

Key Words： conditional value at risk；power battery；closed-loop supply chain network；uncertainty genetic algorithm

0 引言

在国家的倡导和支持下，新能源汽车数量大幅增加，动力电池报废量随之增加。（剩余12536字）