Multi-Objective Modeling of a Reverse Supply Chain by Robust in the Uncertainty of Demand Conditions Using a Meta-Heuristic Algorithm (NSGA-II) in Steel Industry
Volume 8, Issue 4, Winter 2019, Pages 242-258
Ahmad Jafarnejad Chaghooshi, Hannan Amoozad Mahdiraji, Seyedhossein Razavi Hajiagha, Amir Karegar Soltanabad
Abstract Abstract: In design of the supply chain, the use of returned products and their re-cycles in the production and consumption network is called reverse logistics. The proposed model aims to optimize the flow of materials in the supply chain network, determining the amount and location of facilities and planning of transportation in conditions of uncertainty of demand. So that: Maximize total profit of operation, Minimize Adverse environmental effects, Maximize customer & supplier service level. In order to deal with the uncertainty of the model, a scenariobased robust planning is used and to solve the model with the actual data of the case study in the steel industry, a meta-heuristic algorithm (NSGA-II) is utilized. The results of the model obtained from the actual data set and data validation indicate that the model can be integrated in optimizing the objectives and determining the amount and location of the necessary facilities in the steel industry.