Design of reverse supply chains under uncertainty: the lexicographic R_* criterion for exploring opportunities

Abstract

Reverse supply chains (RSCs) have been increasingly implemented in recent years to manage the growing flow of solid waste generated by end-of-life (EOL) products and  to minimise their environmental impact. Furthermore, recent research has shown that the implementation of RSCs benefits job creation, enables savings in raw materials, and creates income from the sales of re-manufactured products. However, designing RSCs requires dealing with many sources of uncertaintydue to the reverse flow of EOL products. To model these uncertainties, we consider  a set of equally possible scenarios. In previous models for scenario sets, the decision often has been influenced by negative scenarios while neglecting opportunities. We propose a new risk/opportunity approach based on the $R_{\ast }$ criterion to give more weight to positive scenarios in the decision-making process. This criterion is used in order to distinguish zones of risk and opportunity and guide the decision-making process accordingly to the existing zones. We develop a lexicographic approach for the consideration of existing scenarios, and propose two methods to compute the optimal solution for lexicographic $R_{\ast }$ ($Lexi{R}_{\ast }$) criterion: one  in the form of an algorithm and another in the form of a mixed-integer program (MIP). The performance of the developed approaches is demonstrated in a case study for a reverse facility location problem.

Keywords:

• Supply chain
• uncertainty
• reverse logistics
• decision making
• robust optimization

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 This article is an extended version of a conference paper (Krug, Guillaume, and Battaïa 2019), that includes a new formulation of the lexicographic $R_{\ast }$ criterion in the form of a mixed-integer program (MIP) as well as a deeper analysis of the results

Additional information

Notes on contributors

Zoé Krug

Zoé Krug is an assistant professor at Université Jean Jaurès in Toulouse, France. The main topic of her research is the strategical design of reverse supply chains and closed-loop supply chains under uncertainty in the context of the development of the circular economy.

Romain Guillaume

Romain Guillaume is an Associate Professor at the University of Toulouse and Institut de Recherche en Informatique de Toulouse (IRIT). His research concerns the management and decision under uncertainty. One of his application concerns the supply chain management.

Olga Battaïa

Prof. Olga Battaïa has a Full Professor position in Department of Operations Management and Information Systems at Kedge Business School. She obtained her PhD form the Ecole des Mines de Saint-Etienne in France in 2007, for which she was granted the Best PhD Thesis Award by the French Research Cluster on Modelling, Analysis and Management of Dynamic Systems. She serves as Associated Editor for several international peer-reviewed journals, including the Journal of Manufacturing Systems, IISE Transactions and Omega-the International Journal of Management Science. She is also a Member of IFAC Technical Committee 5.2. Manufacturing Modelling for Management and Control. Her research interests lie in the domains of Supply Chain Management, Sustainable manufacturing, Operations Research, Combinatorial optimisation, Decision Support Systems. Olga Battaïa co-authored more than 200 scientific publications, participated in several European research projects and was involved in organising several renowned international conferences across Europe and other countries.