Robust Multi-Objective Sustainable Reverse Supply Chain Planning: An Application in the Steel Industry

Autor: Ahmad Jafarnejad, Jurgita Antucheviciene, Hannan Amoozad Mahdiraji, Amir Kargar, Seyyed Hossein Razavi Hajiagha
Rok vydání: 2020
Předmět:
Zdroj: Symmetry, Vol 12, Iss 594, p 594 (2020)
Symmetry; Volume 12; Issue 4; Pages: 594
ISSN: 2073-8994
DOI: 10.3390/sym12040594
Popis: In the design of the supply chain, the use of the returned products and their recycling 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 (SCN), and determine the amount and location of facilities and the planning of transportation in conditions of demand uncertainty. Thus, maximizing the total profit of operation, minimizing adverse environmental effects, and maximizing customer and supplier service levels have been considered as the main objectives. Accordingly, finding symmetry (balance) among the profit of operation, the environmental effects and customer and supplier service levels is considered in this research. To deal with the uncertainty of the model, scenario-based robust planning is employed alongside a meta-heuristic algorithm (NSGA-II) to solve the model with actual data from a case study of the steel industry in Iran. The results obtained from the model, solving and validating, compared with actual data indicated that the model could optimize the objectives seamlessly and determine the amount and location of the necessary facilities for the steel industry more appropriately.
This article belongs to the Special Issue Uncertain Multi-Criteria Optimization Problems
Databáze: OpenAIRE
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