Solving Multiobjective Fuzzy Binary Integer Linear Fractional Programming Problems Involving Pentagonal and Hexagonal Fuzzy Numbers

In this paper, we studied a multiobjective linear fractional programming (MOLFP) problem with pentagonal and hexagonal fuzzy numbers, while the decision variables are binary integer numbers. Initially, a multiobjective fuzzy binary integer linear fractional programming (MOFBILFP) problem was transfo...

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Published in:Journal of Mathematics Vol. 2024; no. 1
Main Authors: Akate, Adane, Fentaw, Getaye
Format: Journal Article
Language:English
Published: Cairo John Wiley & Sons, Inc 2024
Wiley
Subjects:
Algorithms
Approximation
Case studies
Comparative analysis
Decision making
Fuzzy sets
Integer programming
Integers
Investment analysis
Linear programming
Mathematical programming
Methods
Multiple objective analysis
Optimization
Production planning
Set theory
Skewness
Software
Statistics
System theory
ISSN:2314-4629, 2314-4785
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Abstract In this paper, we studied a multiobjective linear fractional programming (MOLFP) problem with pentagonal and hexagonal fuzzy numbers, while the decision variables are binary integer numbers. Initially, a multiobjective fuzzy binary integer linear fractional programming (MOFBILFP) problem was transformed into a multiobjective binary linear fractional programming problem by using the geometric average method; second, a multiobjective binary integer linear fractional programming (MOBILFP) problem was converted into a binary integer linear fractional programming (BILFP) problem using the Pearson 2 skewness coefficient technique; and third, a BILFP problem was solved by using LINGO (version 20.0) mathematical software. Finally, some numerical examples and case studies have been illustrated to show the efficiency of the proposed technique and the algorithm. The performance of this technique was evaluated by comparing their results with those of other existing methods. The numerical results have shown that the proposed technique is better than other techniques.
AbstractList In this paper, we studied a multiobjective linear fractional programming (MOLFP) problem with pentagonal and hexagonal fuzzy numbers, while the decision variables are binary integer numbers. Initially, a multiobjective fuzzy binary integer linear fractional programming (MOFBILFP) problem was transformed into a multiobjective binary linear fractional programming problem by using the geometric average method; second, a multiobjective binary integer linear fractional programming (MOBILFP) problem was converted into a binary integer linear fractional programming (BILFP) problem using the Pearson 2 skewness coefficient technique; and third, a BILFP problem was solved by using LINGO (version 20.0) mathematical software. Finally, some numerical examples and case studies have been illustrated to show the efficiency of the proposed technique and the algorithm. The performance of this technique was evaluated by comparing their results with those of other existing methods. The numerical results have shown that the proposed technique is better than other techniques.
Audience Academic
Author Fentaw, Getaye
Akate, Adane
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  surname: Fentaw
  fullname: Fentaw, Getaye
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ContentType Journal Article
Copyright COPYRIGHT 2024 John Wiley & Sons, Inc.
Copyright © 2024 Adane Akate and Getaye Fentaw. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0
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SubjectTerms Algorithms
Approximation
Case studies
Comparative analysis
Decision making
Fuzzy sets
Integer programming
Integers
Investment analysis
Linear programming
Mathematical programming
Methods
Multiple objective analysis
Optimization
Production planning
Set theory
Skewness
Software
Statistics
System theory
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Title Solving Multiobjective Fuzzy Binary Integer Linear Fractional Programming Problems Involving Pentagonal and Hexagonal Fuzzy Numbers
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