The optimization of an integrated forward and reverse logistics network based on routing and cross-docking strategy

In recent years, expanding the social responsibility concept, increased environmental considerations, economic incentives, and governmental pressure on manufacturers for waste management have caused organizations to focus on developing Closed-Loop Supply Chains (CLSC) and Reverse Logistics (RL) processes. Adopting these approaches will enable organizations to meet economic, social, and environmental goals simultaneously and consider the manufacturing cycle from supply and production to product reuse. Hence, this study deals with an optimization model within the framework of a multi-echelon, multi-product, and multi-period CLSC with hybrid facilities where cross-docking strategy and vehicle routing with soft time windows have been included. In the problem defined as a MILP model, decisions are made simultaneously at three strategic, tactical, and operational levels. Furthermore, to tackle the NP-hard problem and achieve near-to-optimal results in a reasonable time, two meta-heuristic algorithms, NRGA and MOPSO, are developed, and the algorithms' parameters are tuned using the Taguchi method. Finally, the computational results are examined using performance measures and statistical analysis. A sensitivity analysis is performed regarding the impacts of demand and the rate of returned products on the values of the objective functions.