A new score function based Fermatean fuzzy transportation problem

There are several methods, in literature, for finding the fuzzy optimal solution of fully fuzzy transportation problems (transportation problems in which all the parameters are represented by fuzzy numbers). In this paper, the shortcomings of some existing methods are pointed out and to overcome these shortcomings, two new methods (based on fuzzy linear programming formulation and classical transportation methods) are proposed to find the fuzzy optimal solution of unbalanced fuzzy transportation problems by representing all the parameters as trapezoidal fuzzy numbers. The advantages of the proposed methods over existing methods are also discussed. To illustrate the proposed methods a fuzzy transportation problem (FTP) is solved by using the proposed methods and the obtained results are discussed. The proposed methods are easy to understand and to apply for finding the fuzzy optimal solution of fuzzy transportation problems occurring in real life situations.

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Adaptive algorithm for solving the four-index fuzzy transportation problem

2020 IEEE 6th International Conference on Optimization and Applications (ICOA) ◽

10.1109/icoa49421.2020.9094480 ◽

2020 ◽

Author(s):

Hedid Manal ◽

Zitouni Rachid ◽

Labdai Sami

Keyword(s):

Adaptive Algorithm ◽

Transportation Problem ◽

Fuzzy Transportation Problem

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Multiobjective Transportation Problem Using Fuzzy Decision Variable Through Multi-Choice Programming

International Journal of Operations Research and Information Systems ◽

10.4018/ijoris.2017070105 ◽

2017 ◽

Vol 8 (3) ◽

pp. 82-96 ◽

Cited By ~ 5

Author(s):

Gurupada Maity ◽

Sankar Kumar Roy

Keyword(s):

Transportation Problem ◽

Fuzzy Numbers ◽

Real Variable ◽

Programming Approach ◽

Solution Technique ◽

Decision Variable ◽

Fuzzy Decision ◽

Fuzzy Goal ◽

Fuzzy Transportation Problem ◽

New Formulation

This paper analyzes the study of Multiobjective Transportation Problem (MOTP) under the consideration of fuzzy decision variable. Usually, the decision variable in a Transportation Problem is taken as real variable. But, in this paper, the decision variable in each node is selected from a set of multi-choice fuzzy numbers. Inclusion of multiple objectives into transportation problem with fuzzy decision variable makes it a Multiobjective Fuzzy Transportation Problem (MOFTP). In this paper, a new formulation of mathematical model of MOFTP with fuzzy goal of each objective function is enlisted. Thereafter the solution technique of the formulated model is described through multi-choice goal programming approach. Finally, a numerical example is presented to show the feasibility and usefulness of this article.

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

New Mathematics and Natural Computation ◽

10.1142/s1793005719500066 ◽

2018 ◽

Vol 15 (01) ◽

pp. 95-112 ◽

Cited By ~ 4

Author(s):

Abhishekh ◽

A. K. Nishad

Keyword(s):

Transportation Problem ◽

Fuzzy Numbers ◽

Optimal Solution ◽

Solution Procedure ◽

Ranking Functions ◽

Transportation Problems ◽

Intuitionistic Fuzzy Numbers ◽

Intuitionistic Fuzzy ◽

Fuzzy Environment ◽

Fuzzy Transportation Problem

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.

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