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Vol. 33 No. 69 (2024)
July-September 2024: Open Science at the Service of Engineering

Papers

Comparative Study of Cuckoo-Inspired Algorithms to Solve Large-Scale Continuous Optimization Problems

https://doi.org/10.19053/uptc.01211129.v33.n69.2024.17895

Published 2024-08-15

Carlos-Alberto Cobos-Lozada
University of Cauca image/svg+xml

Henry Muñoz-Collazos
Credit One Bank

Richar Urbano-Muñoz
University of Cauca image/svg+xml

Abstract

Two distinctive behaviors of the cuckoo bird have inspired several metaheuristic algorithms to solve continuous optimizationproblems. In addition to the well-known parasitic breeding behavior that gave rise to several cuckoo search (CS) algorithms, another behavior related to their clustering and the way they locate food sources has given rise to the COA algorithm. As a result, there are several variants to solve continuous optimization problems; however, it is necessary to define which one is the most suitable under specific requirements. This paper compares six of these algorithms, including CS+LEM (proposed in this paper), which consists of a hybridization of the CS algorithm with learning evolutionary models (LEM) using an approach known as “metaheuristics enhanced by artificial intelligence”. Three assessments were performed using a set of 61 continuous test functions: 1) the optimal value achieved with a fixed execution time; 2) the number of objective function evaluations required to reach the global optimum; and 3) the optimal value achieved with a fixed number of objective function evaluations. CS+LEM presents the best results in evaluation 1, while COA presents the best results in evaluations 2 and 3. The results were analyzed using the Friedman and Wilcoxon nonparametric statistical tests.

Keywords

artificial intelligence, Cuckoo search algorithm, large-scale continuous problems, metaheuristics, optimization

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Author Biography

Carlos-Alberto Cobos-Lozada

Profesor de Planta Titular Tiempo Completo

Departamento de Sistemas

Facultad de Ingeniería Electrónica y Telecomunicaciones

Universidad del Cauca

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