Optimal Design Of Remanufacturing Reverse Logistics Network In Uncertain Environment

Remanufacturing is the transformation of used products into products, which satisfy exactly the same quality and other standards as new products. Remanufacturing is accomplished through necessary disassembly, examination and repair as well as replacement of components and parts. It is applicable to many kinds of products such as automobile, computer, printer, photocopier, mobile telephone, TV set, refrigerator, air-condition, washing machine, tire, printed circuit board and etc. In the face of limited natural resources and the disposal capacity of waste, remanufacturing being one of advanced forms of product recovery can realize efficiently the synthetical goal of optimal utilization of natural resources, environmental protection and sustainable development of economics. So it has received extensive attention from industrially advanced countries and become one of the most efficient approaches that realize the sustainable development. However, the efficient implement of remanufacturing needs appropriate logistics network structures. Whether the design of remanufacturing logistics network is reasonable or not decides fundamentality the efficiency of logistics management for remanufacturing. Although important contributions have been made to research in the field of the design of traditional production/distribution networks, research on the logistics network design for remanufacturing is still in the initial phase. There are many similar aspects between remanufacturing logistics networks and traditional production/distribution networks, but the former is more complicated owning to its inherent characteristics. Therefore, it is essential to do an in-depth study about the design problem of remanufacturing logistics networks.Based on the existing literatures and aiming at the characteristics of remanufacturing logistics networks, the optimal design of remanufacturing logistics networks based on third-party logistics and manufacturing enterprises are studied respectively. The main contents of this dissertation are as follows:(1) Based on summarizing the relative literatures, the developing progress of the design of remanufacturing logistics networks at home and abroad is reviewed. The shortcomings of existing research on the problem are pointed out and the research ideas of this dissertation are put forward.(2) Form the perspective of third-party logistics in uncertain environment, a stochastic programming model for remanufacturing reverse logistics network is proposed. These uncertain factors involve the quantities and qualities of recycled products and the demanded quantities of products for the clients. Considering the balance of the demand of the clients, the quondam distribution centers of forward logistics network can supply products to the clients. The algorithm for solving the model using the method of expected value method combined with chance constrained programming was proposed. Finally, Simulation results and the analysis with different confidence levels demonstrated the validity and the stability of the model.(3) To reduce logistics cost and improve logistics efficiency, an optimization model for designing integrated product distribution/return logistics network in manufacturing enterprises was proposed based on uncertain programming approach. According to the model, the number of various facilities, their locations and the allocation of the corresponding logistics flows could be decided. The characteristics of the model were as follow: it is proposed that recycled product s were divided into two sorts , remanufacturabel products and waste ones , according to their qualities , the demanded quantities of product and the quantities of those recycled products were taken as random variables, moreover, various rate in network were taken as fuzzy variables. A hybrid intelligent algorithm, based on stochastic simulation, fuzzy simulation and genetic algorithm, is submitted to solve the model and make the model to better reflect the actual situation. Finally, the validity of the model and algorithm is demonstrated by a case study.