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Solution of a pollution sensitive supply chain model under fuzzy approximate reasoning
Author(s) -
De Sujit Kumar,
Bhattacharya Kousik,
Roy Biswajit
Publication year - 2021
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.22522
Subject(s) - fuzzy logic , rework , computer science , mathematical optimization , sensitivity (control systems) , supply chain , extension (predicate logic) , defuzzification , fuzzy set operations , fuzzy set , membership function , fuzzy number , artificial intelligence , mathematics , engineering , programming language , electronic engineering , law , political science , embedded system
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.