A novel population-based metaheuristic algorithm inspired by chaotic dynamics, called chaotic evolution optimization (CEO), is proposed. The main inspiration for CEO is derived from the chaotic evolution process of a two-dimensional discrete memristive map. By leveraging the hyperchaotic properties of the memristive map, the CEO algorithm is mathematically modeled to introduce random search directions for evolutionary processes. Then, the CEO is developed by integrating the crossover and mutation operations from the differential evolution (DE) framework.
引用格式
Yingchao (2026). Chaotic evolution optimization (https://ww2.mathworks.cn/matlabcentral/fileexchange/183362-chaotic-evolution-optimization), MATLAB Central File Exchange. 检索时间: .
MATLAB 版本兼容性
创建方式
R2025b
兼容任何版本
平台兼容性
Windows macOS Linux标签
| 版本 | 已发布 | 发行说明 | |
|---|---|---|---|
| 1.0.0 |
