Heuristic-based metaheuristics to address a sustainable supply chain network design problem

• Published in: Journal of industrial and production engineering Vol. 35; no. 2; pp. 102 - 117
• Main Authors: Samadi, A., Mehranfar, N., Fathollahi Fard, A. M., Hajiaghaei-Keshteli, M.
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 17.02.2018; Taylor & Francis Ltd
• Subjects: Algorithms; Automobile industry; closed-loop supply chain; Genetic algorithms; Heuristic; Heuristic methods; heuristic techniques; Network design; Performance enhancement; red deer algorithm; Response surface methodology; Social factors; Supply chains; Sustainable development; Sustainable developments
• ISSN: 2168-1015; 2168-1023
• DOI: 10.1080/21681015.2017.1422039

Nowadays, the world faces the issue of sustainable integrated business network. Sustainable development attracts both researchers and industrial practitioners who are focused on the Supply Chain Network Design (SCND). In this regard, all economic, environment, and social factors should be considered. Contrary to previous works, this paper addresses a sustainable closed-loop supply chain network problem considering by proposing three new heuristics. To the best of our knowledge, a few related studies have developed heuristics to find best solutions via metaheuristic. In this regard, three heuristics are utilized as procedures to generate initial population to start the recent and old employed metaheuristics. Red Deer Algorithm (RDA) and Genetic Algorithm (GA) are utilized. In addition, the parameters of algorithm are tuned by Response Surface Method (RSM) with an MODM approach in order to improve the performance of algorithms. The results show the capability of proposed heuristics' solution for RDA.