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

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. (c) 2021 Elsevier B.V. All rights reserved.

Automated summary

Sustainable Supply Chain management integrates economic, environmental, and social goals, but there is no consensus on the compatibility of social and environmental responsibilities with profitability. Multi-objective optimization is a method to address the conflicting nature of these goals effectively.