Search Patterns Based on Trajectories Extracted from the Response of Second-Order Systems

Recently, several new metaheuristic schemes have been introduced in the literature. Although all these approaches consider very different phenomena as metaphors, the search patterns used to explore the search space are very similar. On the other hand, second-order systems are models that present dif...

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Bibliographic Details
Published in:Applied sciences 2021-04, Vol.11 (8), p.3430
Main Authors: Cuevas, Erik, Becerra, Héctor, Escobar, Héctor, Luque-Chang, Alberto, Pérez, Marco, Eid, Heba F., Jiménez, Mario
Format: Article
Language:English
Subjects:
Behavior
Evolution
evolutionary methods
metaheuristic methods
Optimization
Optimization algorithms
Physics
Search methods
search patterns
second-order systems
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Summary:Recently, several new metaheuristic schemes have been introduced in the literature. Although all these approaches consider very different phenomena as metaphors, the search patterns used to explore the search space are very similar. On the other hand, second-order systems are models that present different temporal behaviors depending on the value of their parameters. Such temporal behaviors can be conceived as search patterns with multiple behaviors and simple configurations. In this paper, a set of new search patterns are introduced to explore the search space efficiently. They emulate the response of a second-order system. The proposed set of search patterns have been integrated as a complete search strategy, called Second-Order Algorithm (SOA), to obtain the global solution of complex optimization problems. To analyze the performance of the proposed scheme, it has been compared in a set of representative optimization problems, including multimodal, unimodal, and hybrid benchmark formulations. Numerical results demonstrate that the proposed SOA method exhibits remarkable performance in terms of accuracy and high convergence rates.
ISSN:2076-3417
2076-3417
DOI:10.3390/app11083430