Implementing a combined defuzzification: evaluation of COBYLA and SLSQP

Abstract The combined defuzzification of multiple fuzzy sets under a shared constraint is an extension of traditional defuzzification. The problem concerns defuzzifying multiple fuzzy sets at once, adhering to a constraint that involves their defuzzified values. This specific problem emerged in an application of fuzzy rulebase systems with the goal of regridding spatial data; the constraint stems from the need to keep the total modelled value over a region consistent. Through the introduction of goal functions, the combined defuzzification problem was translated to an optimization problem; the goal functions allow to use objective criteria to evaluate and rank different solutions. Different goal functions for the combined defuzzifier have been presented in the relevant literature, in this contribution, the aim is to evaluate solvers in order to develop a usable implementation of the novel defuzzifier and to verify their stability and performance for the presented problem.

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Publication Details

Journal
Control and Cybernetics
Published
2025-09-01
DOI
https://doi.org/10.2478/candc-2025-0011
Primary Topic
Constraint Satisfaction and Optimization
Type
article
Field-Weighted Citation Impact
0.00
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article

Implementing a combined defuzzification: evaluation of COBYLA and SLSQP

Jörg Verstraete, Weronika Radziszewska, Jolanta Jarnicka
Control and Cybernetics
Constraint Satisfaction and Optimization
article

Implementing a combined defuzzification: evaluation of COBYLA and SLSQP

Jörg Verstraete, Weronika Radziszewska, Jolanta Jarnicka
article en

Abstract

Abstract The combined defuzzification of multiple fuzzy sets under a shared constraint is an extension of traditional defuzzification. The problem concerns defuzzifying multiple fuzzy sets at once, adhering to a constraint that involves their defuzzified values. This specific problem emerged in an application of fuzzy rulebase systems with the goal of regridding spatial data; the constraint stems from the need to keep the total modelled value over a region consistent. Through the introduction of goal functions, the combined defuzzification problem was translated to an optimization problem; the goal functions allow to use objective criteria to evaluate and rank different solutions. Different goal functions for the combined defuzzifier have been presented in the relevant literature, in this contribution, the aim is to evaluate solvers in order to develop a usable implementation of the novel defuzzifier and to verify their stability and performance for the presented problem.

Control and CyberneticsVol. 54(3)
Institute of Fluid Flow-Machinery (PL), Systems Research Institute (PL), Polish Academy of Sciences (PL)
Openalex Percentile: Top 29%
Constraint Satisfaction and Optimization
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