Paper Info
Title
Solution Of A Pollution Sensitive Supply Chain Model Under Fuzzy Approximate Reasoning
Abstract
This article develops a three-layer supply chain (SC) pollution dependent production transportation model with rework on fuzzy approximate reasoning approach. First of all, we develop a cost function of the model of reworkable items, in which pollution generates due to transportation of goods only. The aim of this study is to reduce the aggregated pollution level that simultaneously could optimize the integrated SC cost function under fuzzy approximate reasoning. Basically, the theory of two-tailed (randomized L-R fuzzy) approximate reasoning is introduced first time on demand rate in this model which is an extension of one-tailed (randomized L-fuzzy/R-fuzzy) approximate reasoning in the perspectives of the proposed model. An application of a new heart like approximate dual feasible region has also been utilized here also. However, a comparative study has been made taking numerical examples for crisp, general fuzzy, one- and two-tailed fuzzy approximate reasoning models exclusively. Finally, few numerical analyses with sensitivity and graphical discussions are done to legitimize the model.
Year
DOI
Venue
2021
10.1002/int.22522
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
Keywords
DocType
Volume
defuzzification, pollution, rework, supply chain, two-tailed fuzzy approximate reasoning
Journal
36
Issue
ISSN
Citations 
10
0884-8173
1
PageRank 
References 
Authors
0.35
0
3
Name
Order
Citations
PageRank
Sujit Kumar De1438.01
Kousik Bhattacharya210.35
Biswajit Roy310.35