Fuzzy decision making approximation to closed loop supply chain problem

Decision making problems are experienced in every stage of our lives and thefore there exists a continuously evolving literature upon these problems. Decision making includes uncertainty due to its nature. It is known that to handle real world via exact mathematical methods and to provide a solution to encountered decision making problems with these methods is difficult.In today?s competitive markets, to optimize the process of delivering the products from suppliers of raw materials to the customers for the firms formalizes an important problem in the literature. Increasingly contaminated world and limited sources of energy in recent years are regarded, it is inevitable for the mathematical models of any supply chain to have an environmentalist perspective. Hence, closed loop supply chain (CLSC) method has an increasing importance. The CLSC network in the implementation chapter comprises of the loop amongst suppliers-factories-warehouses-distribution centers-customers-recycling centers. The situations which are gathering the products used by end-users via cycling centers to incorporate them to the production process again at certain percentages and conveying them to the factories after decompositions for reproduction are dealt with. In this study, a multi-objective linear model is given for the multi-echelon closed loop supply chain and the solution is obtained by utilizing Zimmermann?s ?min? operator with a fuzzy approach in which the minimum satisfactions of objectives are maximized. The model is to determine the locations of facilities and distribution quantity on the network.