#6027. Adaptive chaotic spherical evolution algorithm

July 2026publication date
Proposal available till 28-05-2025
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Journal’s subject area:
Control and Optimization;
Computer Science (all);
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Abstract:
Nature-inspired metaheuristic algorithms are often based on the first-order difference hypercube search style to search for optimum solutions. In contrast, the spherical evolution algorithm (SE) employs a spherical search style. SE is very effective; however, there is still room for improvement. In this study, we added a chaotic local search (CLS) to the SE to improve its performance. This CLS uses information from several chaotic maps and records each instance of success. The recorded historical success information guides the CLS to choose the chaotic map for the next iteration. In our experiment, we compare the chaotic spherical evolution algorithm (CSE) with the original SE and other metaheuristic algorithms. The test set consists of 29 benchmark functions from the CEC20XX benchmark set and 22 real-world optimization problems from the CEC20XX set. Additionally, the new parameter introduced in the CSE has also been briefly discussed.
Keywords:
Chaotic local search; Chaotic map; Chaotic sequence; Historical information; Nature-inspired metaheuristic algorithm; Spherical evolution algorithm

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