Multi-objective mixed-integer linear optimization model for sustainable closed-loop supply chain network: a case study on remanufacturing steering column

Sonu Rajak (), K. E. K. Vimal (), Sricharan Arumugam (), Jagadesan Parthiban (), Swesh Kannan Sivaraman (), Jayakrishna Kandasamy () and Angel Acevedo Duque ()
Additional contact information
Sonu Rajak: National Institute of Technology, NIT-Patna
K. E. K. Vimal: National Institute of Technology, NIT-Patna
Sricharan Arumugam: Vellore Institute of Technology
Jagadesan Parthiban: Vellore Institute of Technology
Swesh Kannan Sivaraman: Vellore Institute of Technology
Jayakrishna Kandasamy: Vellore Institute of Technology
Angel Acevedo Duque: Universidad Autonoma de Chile

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2022, vol. 24, issue 5, No 22, 6507 pages

Abstract: Abstract Industrialization has caused dire consumption of resources and has already caused acute damage to the environment. Due to stringent environmental regulations, organizations are enforced to adopt sustainability strategies such as reuse, repair, reduce, and remanufacturing. To remanufacture products, manufacturing organizations have to transform their supply chains to be closed or circular. In this study, a mathematical model is formulated to transform a traditional linear supply chain into a closed-loop supply chain (CLSC) for an organization located in India. It is accomplished by incorporating remanufacturing with reverse logistics into the supply chain to achieve sustainability thereby satisfying the sustainable development goals (SDGs). A multi-objective mixed-integer linear programming approach was used to formulate the model to optimize the supply chain to improve the operations of manufacturing, recycling, repair, and disposal to minimize the environmental effects and to maximize the net profit of the product. The GAMS optimization software was used to solve the model, and sensitivity analysis was carried out to validate the robustness of the proposed network. The result states that the organization can make profits by adopting the SDGs. Industry can optimize the number of parts to be repaired, dismantled, recycled, and determine the supplier's optimum quantity of parts purchase. Lack of awareness on the potential of sustainable CLSCs is hindering its acceptance in the economy. The proper use of the proposed model not only helps the organization to maximize profit but also minimizes the environmental impact by attaining sustainability. This study is helpful for organizations that are eco-conscious and are willing to balance economic profit and environmental well-being by adopting sustainability in CLSCs.

Keywords: Closed-loop supply chain (CLSC); Remanufacturing; Multi-objective mixed-integer linear programming (MOMILP); Environment modeling; Optimization; Automobile (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s10668-021-01713-5 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:endesu:v:24:y:2022:i:5:d:10.1007_s10668-021-01713-5

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/10668

DOI: 10.1007/s10668-021-01713-5

Access Statistics for this article

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development is currently edited by Luc Hens

More articles in Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().