Authors: Marjan Olfati; Nikbakhsh Javadian
Addresses: Department of Industrial Engineering, Iran University of Science and Technology, University Street, Hengam Street, P.O. Box: 16765163, Tehran, Iran ' Department of Industrial Engineering, Mazandaran University of Science and Technology, Sardaran 12 Street, Sheykh Tabarsi Street, P.O. Box: 734 Babol, Iran
Abstract: Due to the competitive environment, supply chain management is an important subject in the world of economy. It affects all of the activities including products manufacturing, flow between facilities and costs. In this research, a mixed-integer linear programming model is considered which included supplier, plants, demand markets, collection centres, and disposal centre. The closed-loop supply chain model is bi-objective. So, it is solved by the e-constraint method and non-dominated sorting genetic algorithm-II. In order to improve the meta-heuristic algorithm's efficiency, its parameters are tuned by Taguchi method. Afterward, the different dimensions of the model are considered and the problem is rewritten as a single-objective model and solved by LINGO software and the genetic algorithm using MATLAB software to compare the efficiency of the LINGO and meta-heuristic algorithm. In small-scale problems, solving by LINGO software and in large-scale problems, solving by meta-heuristic algorithms are more efficient.
Keywords: closed-loop supply chain; CLSC mixed-integer linear programming; MILP; e-constraint; non-dominated sorting genetic algorithm-II; NSGA-II; Taguchi method.
International Journal of Applied Decision Sciences, 2020 Vol.13 No.3, pp.363 - 385
Received: 24 Jun 2019
Accepted: 01 Sep 2019
Published online: 14 Jul 2020 *