Opposition-based chaotic evolution for optimization

Opposition-based chaotic evolution for optimization

Abstract Evolutionary computation algorithms are widely used for solving complex optimization problems, but their practical performance is often hindered by high computational costs and premature convergence. To address this challenge, we propose an opposition-based chaotic evolution (OBCE) algorith...

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Bibliographic Details
Main Authors: Tianshui Li, Yan Pei
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Evolutionary computation
Chaotic evolution
Opposition-based learning
Single-objective optimization
Multi-objective optimization
Conceptual hybrid rocket engine design
Online Access:https://doi.org/10.1038/s41598-025-09207-4
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https://doi.org/10.1038/s41598-025-09207-4

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