Multiobjective Model and Solution Method for Integrated Forward and Reverse Logistics Network Design for Third-Party Logistics Providers

Reverse logistics—that is, the distribution activities involved in product returns—is receiving growing attention. Because of the difference and interaction between the forward and reverse distributions, how to integrate the forward and reverse channels has become an emerging issue. Few studies have attempted to integrate the forward and reverse distributions. Furthermore, the increasing opportunities for cost savings and customer satisfaction in such integrated distribution have prompted third-party logistics providers (3PLs) to get involved in forward and reverse logistics operations. This paper first develops a multiobjective model considering activities of the 3PLs for forward and reverse distributions simultaneously. Two objectives are included in the proposed model: (a) maximization of the returned products shipped from customers back to the collection facilities and (b) minimization of the total costs associated with the forward and reverse logistics operations. A fuzzy goal programming approach is applied to determine the compromise solution for the multiobjective model. A genetic algorithm with two subalgorithms is then developed to solve the problem. Numerical experiments are presented to demonstrate the applicability of the formulated model and the proposed solution method.