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Generalized Type-2 Fuzzy Logic-Enhanced Mayfly Algorithm for Robust and Adaptive Optimization

delete2026-01-01
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PRE
AI
L
Lizarraga, Enrique
F
Fevrier Valdez *
DOI：10.13053/CyS-30-1-6302delete
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Abstract

Abstract

En 中文
The Mayfly Algorithm (MA) has demonstrated great potential as a metaheuristic for solving complex optimization problems. In this work, we propose the integration of generalized Type-2 fuzzy logic for dynamic parameter adaptation in MA, enabling accurate tuning under uncertain conditions. The proposed method improves convergence, robustness, and solution quality, making it suitable for a wide variety of applications, ranging from engineering and bioinformatics to systems biology and computational modeling. Comparative evaluation with mathematical benchmark functions demonstrates that the incorporation of generalized Type-2 fuzzy logic in MA outperforms traditional variants, highlighting its versatility and effectiveness in addressing diverse and complex optimization challenges.
Keywords:
Generalized type-2
fuzzy logic
mayfly algorithm
uncertainty handling
adaptive optimization

Journal

C
Computacion y Sistemas
IF:
0.4
Papers:
65
Citations:
441

Organization

No organization information available