Research Of Facility Location On Manufacturing/Remanufacturing Integration Logistics Network

With the the huge consumption of natural resources and rapid increase of industrial wastes, the natural environment has been continuously deteriorating since the middle of last century. For the purpose of sustainabled evelopment, manufacturing must minimize the consumption of resources and solve the pollution problems, especially the recycling of the abandoned items. Responding to the strategy of sustainable development, the concept'remanufacturing'emerged as a new technology to deal with the failure and scrapped products.Remanufacturing is defined as the process of reviving discarded products including disassembly, cleaning, checking, repairing and re-assembly. Remanufactured products have the same or near the same function as the new products. There are mainly three facets to show its environmental benign of remanufacturing as follows. Firstly, remanufacturing reuses many components of the discarded product and directly reduces the quantity of the waste; secondly, Remanufacturing makes full use of the used components instead of new ones to reduce the demand for original resources and pollutions in the process of production of new products; at last, remanufacturing prolongs the life of product and saves the resource indirectly.The concepts, theories, models and algorithms of facility location related to remanufacturing based on Manufactuering/Remanufacturing (M/R) integration logistics network are proposed in this paper. First, the differences and relationships between remanufacturing and the others are analyzed; some key issues are analyzed such as remanufacturing assessment. Then, the elements, classification, modeling and algorithm of facility location are qualitatively discussed. In addition, the shortest path Problem of the example is solved. And then, facility location models on Directly Reusable Network and M/R Network are proposed respectly. The results indicate that it achieves the convergence of better solutions solved by Genetic Algorithm. The result of facility location affected by the chang of the paraments is quantitatively analyzed. Finally, a summary and outlook are provided.