AccScience Publishing / IJOCTA / Volume 16 / Issue 2 / DOI: 10.36922/IJOCTA025410170
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RESEARCH ARTICLE

Retail reverse supply chain optimization under profit–loss budgetary limitation

Mehmet Erdem Coşkun1† ,  Elkafi Hassini2† ,  Engin Kepenek3*
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1 School of Management, Faculty of Management, Canadian University Dubai, Dubai, United Arab Emirates
2 Operations Management, DeGroote School of Business, McMaster University, Hamilton, Ontario, Canada
3 Department of City and Regional Planning, Faculty of Architecture, Akdeniz University, Antalya, Turkey
†These authors contributed equally to this work.
IJOCTA 2026, 16(2), 732–751; https://doi.org/10.36922/IJOCTA025410170
Received: 6 October 2025 | Revised: 26 January 2026 | Accepted: 6 February 2026 | Published online: 2 April 2026
© 2026 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
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Abstract

Retailers increasingly need decision-support tools to manage unsold inventory under operational and fiscal constraints. In this paper, we develop a reverse supply chain (RSC) model for retailers under profit–loss budgetary limitation. The retail RSC consists of multiple stores, a warehouse, and multiple vendors. Each store carries inventory that is not selling as hoped, and they want to get rid of these unwanted products to replace the space with more productive items. Our model considers two options for how a store can get rid of these products: the retailer can send the products to its warehouse if there is demand at other stores, or send them back to their vendor if there are available vendor funds. However, the retailer operates under a predetermined profit–loss budget that should be utilized as closely as possible within the fiscal cycle. The budgetary limitation is the result of profit–loss that will be incurred due to relocating products within and out of its supply chain system. This budgetary limitation, also known as the “P&L effect” in industry, is decided a year prior to an RSC activity for financial, planning, and/or taxation reasons. We model this problem as a mixed integer linear program and solve test problems using CPLEX. We then develop a heuristic solution algorithm and compare the CPLEX solution results and times with our heuristic. We summarize useful insights into our heuristic and how it can be further developed for similar optimization problems with budgetary constraints. Eventually, we outline future research topics and suggestions for RSC models for retailers.

Graphical abstract
Keywords
Profit–loss
Product returns
Retail returns
Returns management
Reverse supply chain
Funding
None.
Conflict of interest
The authors declare they have no competing interests.
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An International Journal of Optimization and Control: Theories & Applications, Electronic ISSN: 2146-5703 Print ISSN: 2146-0957, Published by AccScience Publishing
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