An efficient Lagrangian-based heuristic to solve a multi-objective sustainable supply chain problem

Camila P.S. Tautenhain, Ana Paula Barbosa-Povoa, Bruna Mota and Mariá C.V. Nascimento

European Journal of Operational Research, 2021, vol. 294, issue 1, 70-90

Abstract: Sustainable Supply Chain (SSC) management aims at integrating economic, environmental and social goals to assist in the long-term planning of a company and its supply chains. There is no consensus in the literature as to whether social and environmental responsibilities are profit-compatible. However, the conflicting nature of these goals is explicit when considering specific assessment measures and, in this scenario, multi-objective optimization is a way to represent problems that simultaneously optimize the goals. This paper proposes a Lagrangian matheuristic method, called AugMathLagr, to solve a hard and relevant multi-objective problem found in the literature. AugMathLagr was extensively tested using artificial instances defined by a generator presented in this paper. The results show a competitive performance of AugMathLagr when compared with an exact multi-objective method limited by time and a matheuristic recently proposed in the literature and adapted here to address the studied problem. In addition, computational results on a case study are presented and analyzed, and demonstrate the outstanding performance of AugMathLagr.

Keywords: Heuristics; Sustainable Supply Chain management; Multi-objective optimization; Lagrangian relaxation; AUGMECON2 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:294:y:2021:i:1:p:70-90

DOI: 10.1016/j.ejor.2021.01.008

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