A sustainable supply chain system with optimal production and lead time strategies under intuitionistic fuzzy demand

B. Karthick

Journal of Management Analytics, 2025, vol. 12, issue 3, 609-633

Abstract: This paper presents an integrated inventory model that examines imperfect production processes in the context of intuitionistic fuzzy demand. Defective products identified during the inspection process undergo rework before being released for sale. The dynamic production system allows for adaptability to the environment, with the production cost tied to the variability in production rates. Acknowledging the substantial carbon dioxide emissions from industries and transportation, the manufacturer aligns item production with carbon emission levels and incurs a corresponding carbon emission tax. Market demand for the item is represented as a triangular intuitionistic fuzzy number due to inherent uncertainty. The primary objective of this study is to minimize the integrated cost function of the proposed model through multivariable calculus. Numerical experiments are conducted to assess the model's performance, and sensitivity analysis is employed to validate the effectiveness of the optimal parameters.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/23270012.2025.2455548 (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:tjmaxx:v:12:y:2025:i:3:p:609-633

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tjma20

DOI: 10.1080/23270012.2025.2455548

Access Statistics for this article

Journal of Management Analytics is currently edited by Li Xu

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