Developing an ant colony approach for green closed-loop supply chain network design: a case study in gold industry

Abstract

The forward/reverse logistics network design is an important and strategic issue due to its effects on efficiency and responsiveness of a supply chain. In practice, it is needed to formulate and solve real problems through efficient algorithms in a reasonable time. Hence, this paper tries to cover real case problem with a multi-objective model and an integrated forward/reverse logistics network design. Further, the model is customized and implemented for a case study in gold industry where the reverse logistics play crucial role. A new solution approach is applied for the proposed 7-layer network of the case study and the solutions are achieved in order solve the current difficulties of the investigated supply chain. This paper seeks to address how a multi objective logistics model in the gold industry can be created and solved through an efficient meta-heuristic algorithm. A green approach based on the CO2 emission is considered in the network design approach. The developed model includes four echelons in the forward direction and three echelons in the reverse. First, an integer linear programming model is developed to minimize costs and emissions. Then, in order to solve the model, an algorithm based on ant colony optimization is developed. The performance of the proposed algorithm has been compared with the optimum solutions of the LINGO software through various numerical examples based on the random data and real-world instances. The evaluation studies demonstrate that the proposed model is practical and applicable and the developed algorithm is reliable and efficient. The results prove the managerial implications of the model and the solution approach in terms of presenting appropriate modifications to the mangers of the selected supply chain. Further, a Taguchi-based parameter setting is undertaken to ensure using the appropriate parameters for the algorithm.