Analyzing The Concept Of Graded K-Preference Integration Representation Method

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Anant Tiwari, Dr. Amit Kumar Vats

Abstract

Generally, the fuzzy set concept could be used to deal with the problems with the qualities of ambiguity as well as vagueness. In the decision making process, the reference comparisons for criteria & options tend to be more appropriate to make use of the linguistic variables rather than crisp values in some instances. Meanwhile, the GMIR technique is utilized for the constrained trouble construction to derive the weights of options & criteria, which accomplishes the extension of fuzzy environment. Here in this paper we will study about some basic terms related to K-preference Graded Integration method. We will discuss the fuzzy inventory models under decision maker’s preference (k-preference), and find the optimal solutions of these models, the optimal crisp order quantity or the optimal fuzzy order quantity.

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How to Cite
Dr. Amit Kumar Vats, A. T. . (2021). Analyzing The Concept Of Graded K-Preference Integration Representation Method. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(5), 866–869. Retrieved from https://turcomat.org/index.php/turkbilmat/article/view/1498
Section
Research Articles