Multi-period green reverse logistics network design: An improved Benders-decomposition-based heuristic approach

K. Nageswara Reddy, Akhilesh Kumar, Alok Choudhary and T. C. Edwin Cheng

European Journal of Operational Research, 2022, vol. 303, issue 2, 735-752

Abstract: There has been extensive academic research on the optimisation of reverse logistics (RL) and closed-loop supply chain (CLSC) network design. However, the existing literature is lacking in several features of practical relevance, and the simultaneous consideration of dynamic characteristics, including the multi-period setting, inventory factors, environmental footprints, and scalability of the application. This shortcoming is primarily due to the challenges associated with computation complexity, mathematical formulation, and the need for a faster solution method to solve such large-scale problems in real-time. In this research, we address these challenges and investigate the multi-facility green RL network design problem, integrating carbon footprint and vehicle selection, entailing allocation between the facilities in the multi-period setting to incorporate the dynamic characteristics. We formulate a mixed-integer linear programming (MILP) model to minimise the total cost, comprising the carbon emission cost due to transport and production at the facilities. We also investigate the effects of carbon emissions and the choice of the vehicle fleet on the network's structure. The novelty of our research lies in the development and application of an exact solution method, namely “Improved Benders Decomposition (IBD)” with several algorithmic enhancements, including a strengthened master problem, valid inequalities, a heuristic, and a multi-stage strategy to accelerate the convergence of the Benders decomposition method. By combining these elements, the proposed IBD solves the MILP model, provides a faster solution methodology with improved convergence of the bounds, and addresses the inherent intractability of the existing problem. We apply our proposed heuristic on a set of 12 problem configurations under distinct scenarios. We show that the proposed IBD heuristic outperforms existing traditional methods in terms of solution quality, computational time, and robustness.

Keywords: Supply chain management; Reverse logistics; Carbon emissions; Vehicle fleet; Benders decomposition; Heuristic (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0377221722002211
Full text for ScienceDirect subscribers only

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:eee:ejores:v:303:y:2022:i:2:p:735-752

DOI: 10.1016/j.ejor.2022.03.014

Access Statistics for this article

European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati

More articles in European Journal of Operational Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().