An integer fuzzy transportation problem

Tada, Minoru; Ishii, Hiroaki

doi:10.1016/0898-1221(96)00044-2

Cited by 26 publications

(8 citation statements)

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“…Dubois and Fortemps [3] surveys refinements of the ordering of solutions supplied by the max-min formulation, namely the discrimin partial ordering and the leximin complete preordering. Different kinds of transportation problems are solved in the articles [5,8,11,12,13] .Dominance of fuzzy numbers can be explained by many ranking methods [1,4,9,19,14]. Of these, Robust's ranking method [10] which satisfies the properties of compensation, linearity and additivity.…”

Section: Introductionmentioning

confidence: 99%

Computing Improved Fuzzy Optimal Hungarian Assignment Problems with Fuzzy Costs Under Robust Ranking Techniques.

Nagarajan¹,

Solairaju²

2010

IJCA

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Section: Introductionmentioning

confidence: 99%

Computing Improved Fuzzy Optimal Hungarian Assignment Problems with Fuzzy Costs Under Robust Ranking Techniques.

Nagarajan¹,

Solairaju²

2010

IJCA

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“…Since then several researchers have proposed the transportation problems in various fuzzy environments. For more details one may refer to the works of Tada and Ishii [40],…”

Section: Introductionmentioning

confidence: 99%

Transportation problem in Fermatean fuzzy environment

Sahoo

2023

RAIRO-Oper. Res.

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Due to the uncertain economic and environmental situations of the society, it is impossible to quantify the supply, demand, and transportation costs of a transportation problem precisely. The purpose of this paper is to address the transportation problem where supply, demand, and transportation costs are Fermatean fuzzy numbers. Numerous approaches to addressing transportation problems with fuzzy parameters have been suggested in the literature to date, but in each of these approaches, the parameters corresponding to the transportation problems are either generalized fuzzy numbers or Pythagorean fuzzy numbers. With the help of Fermatean fuzzy sets (FFSs), a relatively new concept, one can manage ambiguous information more simply throughout the decision-making process. As a result, we have used Fermatean fuzzy parameters to solve the transportation problem in this research. Here, we have developed an algorithm to solve the transportation problem with Fermatean fuzzy parameters and have also solved the problem using the existing method. Then, the optimal value can be obtained using arithmetic operations on Fermatean fuzzy numbers. We have solved a numerical example to demonstrate the proposed methodology, and the obtained results are presented and compared with the existing literature. The importance of the research and the scope of further research are then highlighted.

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“…In 1984, Chanas et al [12] suggested fuzzy transportation problems. Since then many authors test the transportation problems in various fuzzy environments such as integer fuzzy [13], multi-objective [14,15], type-2 fuzzy [16][17][18][19], interval-valued fuzzy fractional [20], interval integer fuzzy [21], interval-valued intuitionistic fuzzy [22]. Moreover, we noticed that there are numerous methods to solve this transportation problem such as extension principle [23], ranking function [24], modified Vogel's approximation method [25], Simplex type algorithm [26], fuzzy linear programming [27], fuzzy Russell's method [28], modified best candidate method [29], zero point and zero suffix methods [30] and so on.…”

Section: Introductionmentioning

confidence: 99%

A Pythagorean fuzzy approach to the transportation problem

Kumar

Edalatpanah

Jha

et al. 2019

Complex Intell. Syst.

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This paper introduces a simplified presentation of a new computing procedure for solving the fuzzy Pythagorean transportation problem. To design the algorithm, we have described the Pythagorean fuzzy arithmetic and numerical conditions in three different models in Pythagorean fuzzy environment. To achieve our aim, we have first extended the initial basic feasible solution. Then an existing optimality method is used to obtain the cost of transportation. To justify the proposed method, few numerical experiments are given to show the effectiveness of the new model. Finally, some conclusion and future work are discussed.Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecomm ons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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An integer fuzzy transportation problem

Cited by 26 publications

References 6 publications

Computing Improved Fuzzy Optimal Hungarian Assignment Problems with Fuzzy Costs Under Robust Ranking Techniques.

Computing Improved Fuzzy Optimal Hungarian Assignment Problems with Fuzzy Costs Under Robust Ranking Techniques.

Transportation problem in Fermatean fuzzy environment

A Pythagorean fuzzy approach to the transportation problem

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