An Ant Colony approach to forward-reverse logistics network design under demand certainty

Abstract

Forward-reverse logistics network has remained a subject of intensive research over the past few years. It is of significant importance to be issued in a supply chain because it affects responsiveness of supply chains. In real world, problems are needed to be formulated. These problems usually involve objectives such as cost, quality, and customers' responsiveness and so on. To this reason, we have studied a single-objective model for an integrated forward/reverse logistics network design. This model includes seven echelons; four echelons in the forward direction and three in the reverse direction. We present an effective algorithm based on ant colony optimization for this NP-hard problems to maximize the benefit. The proposed metaheuristic algorithm is a new approach in the field of closed-loop supply chain network design. Furthermore, the developed model is a three-objective one which regards incomes, costs, and the emissions of CO2. A new approach is utilized in order to integrate three various-dimension objective functions. The performance of the proposed algorithm has been compared utilizing the optimum solutions of the LINGO software. Besides, various instances with small, medium, and large sizes are generated and solved so as to make the evaluation of the algorithm reliable. The obtaining results clearly demonstrate superiority performance of the proposed algorithm.