Abstract
Inspired by the observation of crested ibis foraging behavior, we propose a novel bio-inspired optimization algorithm called Crested Ibis Algorithm (CIA). We designed different exploration strategies by simulating the success or failure of ibis foraging and the escape behavior of fish from ibis foraging. Moreover, the dynamic balance between exploration and exploitation was realized through the information interaction mechanism of the two populations. To validate the performance of the proposed CIA algorithm, we conducted comparative experiments with 14 competitive algorithms on different dimensions of the CEC2017 and CEC2022 benchmark suites and showed excellent performance. In addition, we extend the CIA algorithm to the problem of Human-Powered Aircraft Design optimization (HPA). Experiments and statistical tests demonstrate the proposed CIA's superb performance and outstanding robustness. The source code is available at https://github.com/RuiZhong961230/CIA.
Original language | English |
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Article number | 113020 |
Journal | Knowledge-Based Systems |
Volume | 310 |
DOIs | |
State | Published - 2025/02/15 |
Keywords
- Bio-inspired algorithm
- Crested ibis algorithm (CIA)
- Evolutionary computation (EC)
- Predatory behaviors
ASJC Scopus subject areas
- Software
- Management Information Systems
- Information Systems and Management
- Artificial Intelligence