Exploring the opportunities in establishing a closed-loop supply chain under uncertainty

ABSTRACT

Reverse supply chains (RSC) may provide the benefits of reducing pollution, creating new jobs, and generating income from the recyclable materials. However, their implementation comes with risks and hardly predictable outcomes. The model presented in this paper aims to help managers to better evaluate risks and opportunities while deciding on the RSC design to manage the reverse flow of end-of-life (EOL) products in an existing supply chain. The goal is to set up the disassembly and recovery facilities and organize the flows between them while maximizing total network profit. We propose a two-stage multi-period mixed-integer program where the budget available for decisions at each period depends on the outcomes of previous periods. The demand for EOL products, the quantity of products returned and the time required to reprocess these products are considered uncertain. To incorporate this uncertainty into the decision making process, a discrete set of scenarios is defined. To take into account the decision maker's behavior in the areas of risks and opportunities, we propose to use $R_{\ast }$ criterion to select the final solution. To demonstrate the relevance of $R_{\ast }$ criterion, we conduct numerical investigations on an adapted case study from the literature and do a comparison with classic well-known criteria.

Keywords:

• Supply chain
• uncertainty
• reverse logistics
• closed-loop supply chain
• robust optimization

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 The uniform distribution was selected over a normal distribution or a mean value because it better illustrates the lack of information of the decision maker about the behaviour of the uncertain parameters.

Additional information

Notes on contributors

Zoé Krug

Zoé Krug is a PhD Student at ISAE-SUPAERO in the Department of Complex Systems Engineering The main topic of her research is the stategical design of reverse supply chain 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

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.