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

Zoé Krug, Romain Guillaume and Olga Battaïa

International Journal of Production Research, 2021, vol. 59, issue 11, 3221-3236

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_* $R∗ 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_* $R∗ ( $LexiR_* $LexiR∗) 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.

Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2020.1866782 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:59:y:2021:i:11:p:3221-3236

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20

DOI: 10.1080/00207543.2020.1866782

Access Statistics for this article

International Journal of Production Research is currently edited by Professor A. Dolgui

More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().