Hybrid simulated annealing and genetic approach for solving a multi-stage production planning with sequence-dependent setups in a closed-loop supply chain

This paper studies capacitated production planning problem with sequence-dependent setups in a closed-loop supply chain. A multi-stage, multi-period multi-product problem is considered and manufacturing and remanufacturing activities of each product are conducted consequently without additional setup. A mixed integer programming (MIP) model is provided to formulate the problem. In order to solve the model, MIP-based heuristics using rolling horizon are developed which contain non-permutation and permutation heuristics. Moreover, a hybrid simulated annealing (SA) algorithm is proposed in order to solve the problem using a genetic algorithm (GA) to prepare an appropriate initial solution. Taguchi method is used to adjust the parameters of the developed hybrid SA and GA. Finally, the efficiency of the hybrid algorithm versus MIP-based algorithms is demonstrated using computational results. (C) 2017 Elsevier B.V. All rights reserved.