A Hybrid Bio-Inspired Roach Infestation Algorithm with Interval Type-2 Fuzzy Adapter for Large-Scale Optimization: An extensive Evaluation
DOI:
https://doi.org/10.61467/2007.1558.2026.v17i3.1377Keywords:
Roach Roach Infestation Optimization, parameter adaptation, interval type-2 fuzzy logic, Adaptive hybrid metaheuristics, adaptación de parámetros, lógica difusa de tipo 2 por intervalos, metaheurísticas híbridas adaptativasAbstract
The Swarm-based metaheuristic algorithms have been widely adopted for solving large-scale optimization problems due to their flexibility and population-based search mechanisms. Within this family, Roach Infestation Optimization (RIO) leverages collective interactions and hunger-related dynamics to promote global exploration. Despite these advantages, its search behavior is highly sensitive to parameter settings, especially in high-dimensional spaces, where an improper balance between exploration and exploitation can reduce convergence efficiency. This study presents an adaptive strategy based on Interval Type-2 Fuzzy Logic (IT2FL) to regulate the key RIO parameters, C_maxand C_o, according to the evolutionary state of the search process. By explicitly modeling uncertainty in the parameter adaptation mechanism, the proposed framework enables smoother and more robust adjustments compared to static configurations and Type-1 fuzzy approaches. The proposed method is evaluated on large-scale benchmark optimization problems with dimensionalities ranging from 50 to 500. Its performance is systematically compared to the original RIO algorithm, a Type-1 fuzzy-enhanced RIO variant, Cuckoo Search, and Particle Swarm Optimization (PSO). Experimental results demonstrate consistent improvements in solution quality, convergence stability, and robustness across different problem instances. Furthermore, the statistical significance of the observed improvements is validated through statistical analysis based on Z-tests, confirming the effectiveness of the proposed IT2FL adaptation in high-dimensional optimization scenarios.
Spanish-language metadata / Metadatos en español
Título en español:
Un algoritmo híbrido bioinspirado para la infestación de cucarachas con un adaptador difuso de tipo 2 por intervalos para la optimización a gran escala: una evaluación exhaustiva
Resumen:
Los algoritmos metaheurísticos basados en enjambres se han adoptado ampliamente para resolver problemas de optimización a gran escala debido a su flexibilidad y a sus mecanismos de búsqueda basados en poblaciones. Dentro de esta familia, el algoritmo RIO (Roach Infestation Optimization) aprovecha las interacciones colectivas y las dinámicas relacionadas con el hambre para fomentar la exploración global. A pesar de estas ventajas, su comportamiento de búsqueda es muy sensible a la configuración de los parámetros, especialmente en espacios de alta dimensión, donde un desequilibrio entre exploración y explotación puede reducir la eficiencia de la convergencia. Este estudio presenta una estrategia adaptativa basada en la lógica difusa de tipo 2 por intervalos (IT2FL) para regular los parámetros clave del RIO, C_max y C_o, de acuerdo con el estado evolutivo del proceso de búsqueda. Al modelar explícitamente la incertidumbre en el mecanismo de adaptación de parámetros, el marco propuesto permite ajustes más suaves y robustos en comparación con las configuraciones estáticas y los enfoques difusos de tipo 1. El método propuesto se evalúa en problemas de optimización de referencia a gran escala con dimensionalidades que oscilan entre 50 y 500. Su rendimiento se compara sistemáticamente con el algoritmo RIO original, una variante RIO mejorada con lógica difusa de tipo 1, la búsqueda del cuco y la optimización de enjambres de partículas (PSO). Los resultados experimentales demuestran mejoras consistentes en la calidad de la solución, la estabilidad de la convergencia y la robustez en diferentes instancias del problema. Además, la significación estadística de las mejoras observadas se valida mediante un análisis estadístico basado en pruebas Z, lo que confirma la eficacia de la adaptación IT2FL propuesta en escenarios de optimización de alta dimensión.
Palabras Claves:
adaptación de parámetros, lógica difusa de tipo 2 por intervalos, metaheurísticas híbridas adaptativas
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