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Chinese Pangolin Optimizer: a novel bio-inspired metaheuristic for solving optimization problems

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Abstract

This paper proposes a novel bio-inspired metaheuristic algorithm, the Chinese pangolin optimizer (CPO), which draws inspiration from the unique hunting behaviors of Chinese pangolins. Chinese pangolins, leveraging their acute sense of smell and innate hunting instincts, can precisely perceive the distance between themselves and their prey, enabling efficient transitions between luring and predation behaviors. The luring behavior consists of two stages: attracting and capturing and moving to feed, while the predation behavior involves three stages: searching and locating, rapid approaching, and digging to feed. These behaviors were successfully simulated through mathematical modeling, and the algorithm’s convergence was systematically analyzed using Markov chain theory, theoretically ensuring the efficiency and reliability of the algorithm in the optimization process. To comprehensively evaluate the performance of the CPO algorithm, 74 standard benchmark functions were utilized, covering unimodal, multimodal, and fixed-dimension multimodal functions, as well as the CEC2017, CEC2019, and CEC2022 test suites. The experimental results and statistical analyses indicate that the CPO algorithm is effective and convergent when addressing complex numerical optimization problems. The CPO algorithm was also successfully applied to three standard engineering design optimization problems and twelve feature selection tasks, further validating its broad applicability and scalability in real-world problems. The experimental results demonstrate that the CPO algorithm outperforms various baseline metaheuristic algorithms and mainstream feature selection methods regarding optimization performance and classification accuracy, fully showcasing its broad applicability and superiority in solving complex real-world problems. Source codes of CPO are publicly available at https://ww2.mathworks.cn/matlabcentral/fileexchange/178109-chinese-pangolin-optimizer.

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No datasets were generated or analyzed during the current study.

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Acknowledgements

This research was funded by the National Natural Science Foundation of China (52374123).

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Authors and Affiliations

  1. College of Mining, Liaoning Technical University, Fuxin, 123000, Liaoning, China

    Zhiqing Guo & Guangwei Liu

  2. College of Science, Liaoning Technical University, Fuxin, 123000, Liaoning, China

    Feng Jiang

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  1. Zhiqing Guo
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  2. Guangwei Liu
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  3. Feng Jiang
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Contributions

Zhiqing GUO: Conceptualization, Methodology, Software, Validation, Investigation, Formal analysis, Writing-Original Draft, Writing-Review and Editing, Visualization. Guangwei LIU: Investigation, Writing-review and editing, Supervision, Project administration, Funding acquisition. Feng JIANG: Software, Formal analysis, Investigation, Data curation.

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Correspondence to Guangwei Liu.

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Guo, Z., Liu, G. & Jiang, F. Chinese Pangolin Optimizer: a novel bio-inspired metaheuristic for solving optimization problems. J Supercomput 81, 517 (2025). https://doi.org/10.1007/s11227-025-07004-4

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