A Novel Ranking Approach to Solving Fully LR-Intuitionistic Fuzzy Transportation Problems

Abhishekh and A. K. Nishad ()
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Abhishekh: Department of Mathematics, Institute of Science, Banaras Hindu University, Varanasi 221005, Uttar Pradesh, India
A. K. Nishad: #x2020;School of Basic and Applied Sciences, Shobhit University, Gangoh 247341 Uttar Pradesh, India

New Mathematics and Natural Computation (NMNC), 2019, vol. 15, issue 01, 95-112

Abstract: To the extent of our knowledge, there is no method in fuzzy environment to solving the fully LR-intuitionistic fuzzy transportation problems (LR-IFTPs) in which all the parameters are represented by LR-intuitionistic fuzzy numbers (LR-IFNs). In this paper, a novel ranking function is proposed to finding an optimal solution of fully LR-intuitionistic fuzzy transportation problem by using the distance minimizer of two LR-IFNs. It is shown that the proposed ranking method for LR-intuitionistic fuzzy numbers satisfies the general axioms of ranking functions. Further, we have applied ranking approach to solve an LR-intuitionistic fuzzy transportation problem in which all the parameters (supply, cost and demand) are transformed into LR-intuitionistic fuzzy numbers. The proposed method is illustrated with a numerical example to show the solution procedure and to demonstrate the efficiency of the proposed method by comparison with some existing ranking methods available in the literature.

Keywords: LR fuzzy number; LR-intuitionistic fuzzy number (LR-IFN); ranking function; LR-intuitionistic fuzzy transportation problem (LR-IFTP) (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1142/S1793005719500066

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