A multi-objective reverse logistics network design model for after-sale services and a tabu search based methodology

Reverse logistics has become one of the emerging research and application areas since the early 1990s due to several driving forces such as economic benefits, governmental regulations, increasing levels of environmental problems, etc. As an essential part of reverse logistics (RL) literature, Reverse Logistics Network Design (RLND) efforts can provide economic and ecological advantages to the supply chains. In this study, we consider a reverse distribution channel and try to determine the locations of the collection centers (CCs) and repair centers (RCs) and the amount of product flow between the customers-CCs and CCs-RCs. Considering the multi-objective nature of the RLND problems, total cost and total delay minimization and total average capacity utilization maximization objectives are taken into account. This problem is formulated as a multi-objective mixed integer nonlinear programming model and is solved by two approaches: a heuristic and a tabu search based meta-heuristic in which both of the solution approaches are integrated with weighted max-min approach. Numerical analyses have been carried out to show the effectiveness of the proposed approaches and the solutions obtained from each approach have been compared.