Deterministic and Metaheuristic Solutions for Closed-loop Supply Chains with Continuous Price Decrease

In a global economy, an efficient supply chain as the main core competency empowers enterprises toprovide products or services at a right time in a right quantity, and at a low cost. This paper is to plan asingle-product, multi-echelon, multi-period closed-loop supply chain for high-tech products (whichhave continuous price decrease). Ultimately, considering components ralated to procurement,production, distribution, recycling and disposal, the final decisions are made. To solve the mixedinteger linear programming model for closed-loop supply chain network plan of the paper, fourheuristics-based methods including genetic algorithm, particle swarm optimization, differentialevolution, and artificial bee colony are proposed. Finally, the computational results of these fourmethods are compared with the solutions obtained by GAMS optimization software. The solutionreveales that the artificial bee colony methodology works well in terms of quality of solutions.