Fuzzy inventory model for deteriorating items in a green supply chain with carbon concerned demand
Smita Rani (),
Rashid Ali and
Anchal Agarwal
Additional contact information
Smita Rani: AKTU University
Rashid Ali: AKTU University
Anchal Agarwal: Amity University
OPSEARCH, 2019, vol. 56, issue 1, No 5, 122 pages
Abstract:
Abstract With the environment deterioration becoming a serious concern, numerous industries have realized that it’s critical to focus on manufacturing with reduced waste and low carbon emission. Studies show that consumers are getting cognizant of environment preservation and prefer low-carbon developed products. It is seen that in some cases, customers are willing to pay even more for products developed using low carbon emission technologies. Furthermore, government initiatives towards going green has resulted in industries focusing on reducing their carbon footprints throughout the supply chain by employing green supply chain methodologies. In this study, we will develop an inventory model for deteriorating items in green supply chain considering recycling, reverse logistics and remanufacturing. Demand is assumed to be carbon dependent. Products are considered to be deteriorating in nature with time dependent deterioration rate. A crisp model is developed to minimize total average cost. In the crisp model, it is assumed that demand, deterioration and returned rate are precisely known. However, in reality these parameters are imprecise in nature. To model this impreciseness, a fuzzy model is developing considering these parameters as triangular fuzzy numbers. Total cost function is defuzzified using signed distance method and is shown to be convex and a unique solution exists. Numerical analysis is carried out for both crisp and fuzzy cases.
Keywords: Green supply chain; Reverse logistics; Carbon dependent demand; Deterioration; Fuzzy model; Signed distance method (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
http://link.springer.com/10.1007/s12597-019-00361-8 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:opsear:v:56:y:2019:i:1:d:10.1007_s12597-019-00361-8
Ordering information: This journal article can be ordered from
http://www.springer. ... search/journal/12597
DOI: 10.1007/s12597-019-00361-8
Access Statistics for this article
OPSEARCH is currently edited by Birendra Mandal
More articles in OPSEARCH from Springer, Operational Research Society of India
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().