Remanufacturing Reverse Logistics Network Design Based On The Third-party Recovery Under Uncertain Environment

Currently, most studies of reverse logistics network focused on the design of reverse logistics network under certain environment. The waste products are mostly recycled by original equipment manufacturers. The objective is usually minimizing the total cost of reverse logistics, with little consideration of maximizing the profit of each subject. The background of this paper is the National Natural Science Foundation which my tutor undertakes. The design of the remanufacturing reverse logistics network based on the third-party recovery under uncertain environment was studied.Main work and results of this paper are as follows:(1) To deal with uncertain quantities of products recovery and the demand of consumer markets, a static located model of multi-period and multi-objective was built. The uncertainty parameters were denoted by the triangular fuzzy numbers. With fuzzy chance constrained programming methods, the network model in the uncertain environment can be transferred into a certain equivalent model. The effect of changes of confidential level on both of the optimal location decisions and total revenue of the manufacturer was analyzed by a numerical example. The relationship between the benefit of both the third-party logistics supplier and the manufacturer was analyzed by goal programming method.(2) Based on the static located model of multi-period and multi-objective, the network was designed from a single manufacturer involved to multiple manufacturers participating in, and from the design of static network to dynamic network. A dynamic located model of multi-period remanufacturing reverse logistics network was established. The uncertainty parameters were denoted by the random parameters. The validity of the model was illustrated by a numerical example, and the relationship between each goal was analyzed by constraint method. The result of the dynamic located model was compared with the static located model.(3) Based on the dynamic located model of multi-period remanufacturing reverse logistics network, and considering the capacity expansion of inspection/disassembly centers and remanufacturing plants, the remanufacturing reverse logistics network that the capacity of facilities can be expanded was built. The maximum benefit of the entire system was gain by weighted method. The total benefit of the third-party logistics supplier and each manufacturer was maximized by the opening or closing state of facilities and numbers of modules that the capacity of each facility can be expanded every period. The utility of the model was illustrated by a numerical example, and solution results of the model of facility capacity can be expanded and the model of facility capacity cannot be expanded were compared.(4) To deal with the solution of more complex model, a hybrid intelligent algorithm consisting of genetic algorithm and simulated annealing algorithm has been designed. The utility of the algorithm was illustrated by the numerical example.