Research On Optimization Of Closed-loop Supply Chain And Optimization Method Of Remanufacturing Job Shop Scheduling

Remanufacturing,one of the effective ways to recycle and reuse waste products,which helps to reduce costs,resource waste and pollution of the environment,has enormous benefits of economic and social.The reverse supply chain generated by the recycling of waste products is combined with the traditional forward supply chain,then a closed-loop supply chain is formed,which maximizes the profit of the system.This paper conducts an in-depth study of the closed-loop supply chain system dynamics model of retailer-led,retailer and third-party hybrid recycling models,optimizing the factors affecting revenue,maximizing the benefits of manufacturers,retailers and supply chains.In order to improve the profit of the supply chain,the system dynamics optimization models of supply chain are constructed by using game theory and system dynamics method.By introducing horizontal coordination optimization and replenishment mechanism between manufacturers,the profit of node enterprises in supply chain can be improved.The fluctuation of market demand and the difficulty of information sharing,a closed-loop supply chain model dominated by retailers is constructed.Two contract mechanisms of market share and the ratio of available inventory to recycled inventory,are used to provide an effective way to increase supply chain revenue.To optimize the chain-to-chain competition on remanufacturing and reuse of the closed-loop supply chain,by analyzing the impact of different recycling channels on recycling,a closed-loop supply chain model of mixed recycling competition dominated by the third party and the retailer is constructed,It can improves the competitiveness of the supply chain dominated by retailers,by optimizing the revenue distribution contract.Aiming at the example of location selection of electronic waste collection point,a particle swarm optimization algorithm based on adaptive adjustment of inertia weight is proposed,which saves the cost of recovery point and improves the efficiency of the recycling.Aiming at the disadvantage that the uncertain processing time of remanufacturing parts leads to scheduling more complex,the uncertain processing time is transformed into definite time by the method of rando m simulation triangular fuzzy number.In order to overcome the blindness of neighborhood search of two processes in random exchange in job shop scheduling,a neighborhood search algorithm for key processes in machine idle time is proposed.Particle swarm optimization and genetic algorithm are combined to optimize the minimum maximum completion time in remanufacturing job shop scheduling.The effectiveness of the algorithm is verified by the standard JSP problem and job shop scheduling examples.