This paper proposes a novel bio-inspired metaheuristic algorithm, called Chinese Pangolin Optimizer (CPO). Drawing inspiration from two distinct hunting behaviors observed in the Chinese pangolin, namely luring and predation, the CPO algorithm embodies these behaviors in five key stages: attraction and capture, movement and feeding, search and localization, rapid approach, and digging and feeding. These stages are mathematically modeled and implemented to facilitate highly efficient optimization within complex search spaces. To validate the performance of the CPO algorithm, a comprehensive evaluation is conducted under standardized experimental conditions, benchmarking its effectiveness against other metaheuristic algorithms using benchmark functions and real-world engineering problems.
引用格式
GUO (2024). Chinese Pangolin Optimizer (CPO) (https://www.mathworks.com/matlabcentral/fileexchange/157086-chinese-pangolin-optimizer-cpo), MATLAB Central File Exchange. 检索来源 .
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参考作品: Grey Wolf Optimizer (GWO), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO)
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版本 | 已发布 | 发行说明 | |
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1.1.0 |