Convexity and level sets for interval-valued fuzzy sets

Huidobro, Pedro; Alonso, Pedro; Janiš, Vladimír; Montes, Susana

doi:10.1007/s10700-021-09376-7

Cited by 6 publications

(3 citation statements)

References 20 publications

(26 reference statements)

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“…Several publications like [8], [26], [9], [11], [35] and [10] in the literature use generalised fuzzy numbers to address practical issues. [20] has found the convexity and level sets for interval-valued fuzzy sets and [17] has performed the cost allocation problems for fuzzy agents in a fixed tree network. In continuation with these proposed works, this paper deals with the distinctive representations of icosagonal fuzzy number with linearity and non-linearity as well as with symmetrical and asymmetrical nature.…”

Section: Introductionmentioning

confidence: 99%

Distinctive representations of icosagonal fuzzy numbers along with novel defuzzification techniques for solving fuzzy assignment problems

Bhadauria

Kumar

et al. 2023

Preprint

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In this paper, we represent icosagonal fuzzy numbers in a variety ofways, both symmetrically and asymmetrically, linearly and non-linearly as well as single valued and interval -valued. Along with this, we have alsodeveloped some defuzzification procedures with different approaches based on centroidmethod, the mean of alpha-cut method and bounded area method. In order todemonstrate the significance of these strategies, defuzzification approaches can be applied to many optimization problems in operational research. We have applied these strategies to solve the numerical example based on fuzzy assignment problem in the interview board panel with twenty parameters. This study deals with the situation where icosagonal fuzzynumbers are used to represent ambiguous information in the form of linguistic terms. The ranking function for icosagonal number is also proposed in this paper for the better comparison of two icosagonal fuzzy numbers and its primary goal is used in this research for the appropriate allocation to resolve the fuzzy assignment problem.

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Section: Introductionmentioning

confidence: 99%

Distinctive representations of icosagonal fuzzy numbers along with novel defuzzification techniques for solving fuzzy assignment problems

Bhadauria

Kumar

et al. 2023

Preprint

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“…In response to the challenge of uncertainty, fuzzy quadratic programming has emerged as a significant approach in mathematical modeling. These models allow optimization while considering uncertainties and ambiguities in specific parameters (Huidobro et al, 2022). Moreover, recent advancements in interval-valued fuzzy sets (IVFS) have garnered attention for their ability to handle more complex uncertainties than conventional fuzzy approaches (Huidobro et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

“…These models allow optimization while considering uncertainties and ambiguities in specific parameters (Huidobro et al, 2022). Moreover, recent advancements in interval-valued fuzzy sets (IVFS) have garnered attention for their ability to handle more complex uncertainties than conventional fuzzy approaches (Huidobro et al, 2022). Through this research, we aim to amalgamate ride-hailing matching with mathematical methods like fuzzy quadratic programming and interval-valued fuzzy concepts.…”

Section: Introductionmentioning

confidence: 99%

Ride-Hailing Assignment Problem under Waiting Time Uncertainty using Interval-Valued Fuzzy Quadratic

Supian,

Subiyanto,

Megantara

et al. 2023

IJGOIA

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Ride-hailing is a creative idea created by transportation supported by science and technology. Ride-hailing services can help daily community activities. The issue with ride-hailing is that traffic conditions are unpredictable, implying that waiting times are uncertain. The time passengers spend waiting from when they book a ride service until the driver arrives at the pick-up location is called waiting time. This study suggests a quadratic programming technique for minimizing waiting time while accounting for the unpredictability of pick-up travel time. The interval-valued fuzzy quadratic programming method handles the uncertainty and imprecision of the anticipated journey time. When allocating drivers to pick up passengers, interval-valued fuzzy numbers can provide a more realistic representation of waiting time uncertainty. As a result, the interval-valued fuzzy quadratic programming model can handle the uncertainty in waiting time for ride-hailing assignment problems. The model's performance is evaluated using waiting time and the number of people served. The model's performance is demonstrated numerically using the simulation-based case study. This study shows how to utilize a mathematical method to solve real-world problems with uncertainty and improve user welfare.

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Interval Type-3 Fuzzy Differential Evolution for Parameterization of Fuzzy Controllers

Ochoa

Castillo

Melín

et al. 2023

Int. J. Fuzzy Syst.

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Convexity and level sets for interval-valued fuzzy sets

Cited by 6 publications

References 20 publications

Distinctive representations of icosagonal fuzzy numbers along with novel defuzzification techniques for solving fuzzy assignment problems

Distinctive representations of icosagonal fuzzy numbers along with novel defuzzification techniques for solving fuzzy assignment problems

Ride-Hailing Assignment Problem under Waiting Time Uncertainty using Interval-Valued Fuzzy Quadratic

Interval Type-3 Fuzzy Differential Evolution for Parameterization of Fuzzy Controllers

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