Alternative Arithmetic of Pentagonal Fuzzy Numbers

Arfina, Intan; adi, Mash

doi:10.14445/22315373/ijmtt-v66i12p505

Cited by 3 publications

(1 citation statement)

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“…Suhailywati Ramli [18] discussed a portfolio selection model that builds on Markowitz's traditional mean-variance model by representing returns as pentagonal fuzzy numbers. Intan Arfina [19] introduced the alternative arithmetic of pentagonal fuzzy numbers on the concept of positive and negative fuzzy numbers. Sapan Kumar Das [20] introduced a new Neutrosophic pentagonal number score function and established a novel method for obtaining initial fundamental workable answers.…”

Section: Introductionmentioning

confidence: 99%

A New Ranking Approach for Solving Fuzzy Transportation Problem with Pentagonal Fuzzy Number

Vidhya¹,

Ganesan²

2022

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In any decision-making process, imprecision is a significant issue. To deal with the ambiguous environment of collective decision-making, various tools and approaches have been created. Fuzzy set theory is one of the most recent approaches for coping with imprecision. The Fuzzy Transportation Problem (FTP) is a well-known network planned linear programming problem which exists in a variety of situations and has received a lot of attention recently. Many authors defined and solved the fuzzy transportation problem with frequently utilized fuzzy numbers such as triangular fuzzy numbers or trapezoidal fuzzy numbers. On the other hand, real-world problems usually involve more than four variables. To tackle these concerns, the pentagonal fuzzy number is applied to the problems. This article proposes an approach to solving transportation problems whose parameters are pentagonal fuzzy numbers without requiring an initial feasible solution. An algorithm based on the core and spread method and an extended MODI method is developed to determine the optimal solution to the problem. The proposed process is based on the approximation method and gives a more efficient result. An illustrated example is used to validate the model. As a result, the proposed methodology is both simpler and more computationally efficient than the existing approaches.

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Section: Introductionmentioning

confidence: 99%