废旧汽车零部件再制造回收模型优化研究

Optimization of remanufacturing-recovery model for used vehicle parts

建立废旧汽车零部件回收与再制造智能交易平台,对我国废车市场的建设和完善以及汽车零部件再制造产业链的发展具有重大的工程实用价值。为研究适用于第三方平台的回收模式和策略,本文构建了由制造商、再制造商、销售商、回收平台和激励政策共同组成的再制造闭环供应链回收模型,通过利润函数来揭示再制造供应链中各企业的定价策略和相关变量的关系。分别利用逆向归纳法和多目标遗传算法求解该模型,并以废旧汽车变速箱为案例,验证和比较了2种算法的可行性和优劣性。仿真分析结果表明,基于多目标遗传算法求解下制定的回收策略优于逆向归纳法,预期闭环供应链整体回收率和企业利润可得到全面优化,为再制造产业链各参与者的回收决策提供了具有现实意义的理论依据。

The establishment of an intelligent trading platform for recycling and remanufacturing of wasted vehicle parts has a great engineering practical value to the contribution of the waste vehicle market and the development of an industrial chain for remanufacturing system.This paper constructs a recycling model of remanufacturing a closed-loop supply chain,which is composed of the manufacturer,remanufacturer,seller,recycling platform and incentive policy.The profit function is used to reveal the relationship between pricing strategy and related variables of each enterprise in remanufacturing supply chain.The backward induction method and multi-objective genetic algorithm are used to solve the recycling model,and the feasibility and advantages of the two algorithms are verified and compared by a case study of wasted vehicle gearboxes.The simulation results show that the recycling strategy based on the multi-objective genetic algorithm is better than the backward induction method,and the overall recovery rate and enterprise profit of the closed-loop supply chain are expected to be comprehensively optimized,which provides a theoretical basis of practical significance for the recycling decision of each participant in the remanufacturing industry chain.