Author
Listed:
- Lisa Bora
(Assam University)
- Nabendu Sen
(Assam University)
- Prabal Das
(Assam University)
Abstract
This study presents a novel dynamic sustainable production-inventory model designed specifically for the fashion industry, distinguishing between traditional and eco-friendly product lines. Unlike existing models, it integrates three key levers—advance payment mechanisms, green investment decisions, and carbon emission penalties—into a unified optimization framework. The model seeks to maximize total profit while minimizing environmental impact, particularly carbon emissions, by incorporating a price- and investment-sensitive demand structure for eco-friendly garments. Advance payment acts as both a liquidity enhancer and an environmental financing mechanism, while green investment directly influences demand and emission intensity. Carbon penalties are imposed when total emissions exceed regulatory thresholds, reinforcing sustainable production. The model includes detailed cost components, such as production, holding, and emission costs. To identify optimal production rates, investment levels, and pricing strategies, two metaheuristic techniques—weighted particle swarm optimization (WPSO) and constriction factor PSO (CPSO)—are employed. Both methods converge to the same global optimum, yielding a maximum profit of INR 4471.0 while satisfying emission constraints. Sensitivity analysis confirms the model’s robustness against variations in key parameters. Overall, the proposed model offers actionable insights for fashion manufacturers seeking to align profitability with circular economy and climate-resilient objectives.
Suggested Citation
Lisa Bora & Nabendu Sen & Prabal Das, 2025.
"A Sustainable Production-Inventory Model for the Fashion Industry: Integrating Advance Payment, Green Investment, and Emission Reduction Strategies,"
SN Operations Research Forum, Springer, vol. 6(4), pages 1-31, December.
Handle:
RePEc:spr:snopef:v:6:y:2025:i:4:d:10.1007_s43069-025-00576-0
DOI: 10.1007/s43069-025-00576-0
Download full text from publisher
As the access to this document is restricted, you may want to
for a different version of it.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:snopef:v:6:y:2025:i:4:d:10.1007_s43069-025-00576-0. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.