On LR-type fully intuitionistic fuzzy linear programming with inequality constraints: Solutions with unique optimal values

Pérez‐Cañedo, Boris

doi:10.1016/j.eswa.2019.03.035

Cited by 19 publications

(23 citation statements)

References 29 publications

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“…An extension of the proposed fuzzy epsilon‐constraint method to fully intuitionistic fuzzy MOLP can be done by generalising the single‐objective case given in Reference .…”

Section: Concluding Remarks and Future Workmentioning

confidence: 99%

“…An extension of the proposed fuzzy epsilon-constraint method to fully intuitionistic fuzzy MOLP can be done by generalising the single-objective case given in Reference. 48 Thus, the obtained intuitionistic fuzzy epsilon-constraint method could be used, for example, to solve a fully intuitionistic version of the intuitionistic fuzzy multiobjective (IFMO) fixed-charge solid transportation problem presented by Roy and Midya. 49 It is interesting to note that Roy and Midya 49 used a linear ranking function to map each intuitionistic fuzzy number into a real number, and transformed the IFMO fixed-charge solid transportation problem into a crisp one, which was then solved via Angelov's method.…”

Section: Casesmentioning

confidence: 99%

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An epsilon‐constraint method for fully fuzzy multiobjective linear programming

2020

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Linear ranking functions are often used to transform fuzzy multiobjective linear programming (MOLP) problems into crisp ones. The crisp MOLP problems are then solved by using classical methods (eg, weighted sum, epsilon‐constraint, etc), or fuzzy ones based on Bellman and Zadeh's decision‐making model. In this paper, we show that this transformation does not guarantee Pareto optimal fuzzy solutions for the original fuzzy problems. By using lexicographic ranking criteria, we propose a fuzzy epsilon‐constraint method that yields Pareto optimal fuzzy solutions of fuzzy variable and fully fuzzy MOLP problems, in which all parameters and decision variables take on LR fuzzy numbers. The proposed method is illustrated by means of three numerical examples, including a fully fuzzy multiobjective project crashing problem.

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“…An extension of the proposed fuzzy epsilon‐constraint method to fully intuitionistic fuzzy MOLP can be done by generalising the single‐objective case given in Reference .…”

Section: Concluding Remarks and Future Workmentioning

confidence: 99%

Section: Casesmentioning

confidence: 99%

An epsilon‐constraint method for fully fuzzy multiobjective linear programming

2020

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“…Pe � rez-Ca� nedo et al [15] developed a method to solve LR-type fully intuitionistic fuzzy linear programming model. We have proposed two methods to solve LR-type FPFLPP with mixed constraints.…”

Section: Comparison With Existing Linear Programming Modelmentioning

confidence: 99%

“…Najafi and Edalatpanah [14] introduced a new method for solving fully fuzzy linear programming problems. Pe �rez-Ca� nedo et al [15] gave a revised version of a lexicographical-based method for solving fully fuzzy linear programming problems with inequality constraints.…”

Section: Introductionmentioning

confidence: 99%

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Methods for Solving $L R$ -Type Pythagorean Fuzzy Linear Programming Problems with Mixed Constraints

Akram

Ullah

Alharbi

2021

Mathematical Problems in Engineering

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A Pythagorean fuzzy set is the superset of fuzzy and intuitionistic fuzzy sets, respectively. Yager proposed the concept of Pythagorean fuzzy sets in which he relaxed the condition that sum of square of both membership degree and nonmembership degree of an element of a set must not be greater than 1. This paper introduces two new techniques to solve L R -type fully Pythagorean fuzzy linear programming problems with mixed constraints having unrestricted L R -type Pythagorean fuzzy numbers as variables and parameters by introducing unknown variables and using a ranking function. Furthermore, we show the equivalence of both the proposed methods and compare the solutions obtained by the two techniques. Besides this, we solve an already existing practical model using proposed techniques and compare the result.

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Empirical Versus Analytical Solutions to Full Fuzzy Linear Programming

Stanojević

2020

Advances in Intelligent Systems and Computing

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On LR-type fully intuitionistic fuzzy linear programming with inequality constraints: Solutions with unique optimal values

Cited by 19 publications

References 29 publications

An epsilon‐constraint method for fully fuzzy multiobjective linear programming

An epsilon‐constraint method for fully fuzzy multiobjective linear programming

Methods for Solving $L R$ -Type Pythagorean Fuzzy Linear Programming Problems with Mixed Constraints

Empirical Versus Analytical Solutions to Full Fuzzy Linear Programming

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On LR-type fully intuitionistic fuzzy linear programming with inequality constraints: Solutions with unique optimal values

Cited by 19 publications

References 29 publications

An epsilon‐constraint method for fully fuzzy multiobjective linear programming

An epsilon‐constraint method for fully fuzzy multiobjective linear programming

Methods for Solving L R -Type Pythagorean Fuzzy Linear Programming Problems with Mixed Constraints

Empirical Versus Analytical Solutions to Full Fuzzy Linear Programming

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Product

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Methods for Solving $L R$ -Type Pythagorean Fuzzy Linear Programming Problems with Mixed Constraints