A Fuzzy Mixed Integer Linear Programming Model for A Reverse Logistics System with A Real Case Application

Abstract

Environmental concerns, providing a decrease in production cost and utility of products and materials constitute reverse logistics activities in recent years. One of the most important goals of the reverse logistics network design is to minimize the costs or to maximize the profit. By the way, deciding on the number of collection centers, fabrics and distribution centers in a reverse logistics system are also very important. Uncertain factors can affect a reverse logistic network negatively. In this paper to cope with these uncertainties a fuzzy mixed integer linear programming model is developed for a reverse logistics network with a real case application on white goods sector refrigerator product group. In the proposed model customers' demand, return rate of products, unit transportation cost and repair cost are considered as uncertain parameters. The proposed model is solved by using General Algebraic Modeling System (GAMS)/CPLEX 9.0 optimization software ant it is executed for different return and repair rates to determine and compare the number of collection centers, fabrics, distribution centers and maximum profit. The obtained results are consistent with each other.