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  4. Vol 10, Issue 1, 2025

A Nature-inspired Fully Enhanced Hybrid Algorithm Based on Intra-group Competition Mechanism

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DOI: 10.23977/jnca.2025.100107 | Downloads: 1 | Views: 88

Author(s)

Rongguo Qu 1, Zhenxing Yu 1, Dewei Yang 1, Jin Su 1, Qinwei Fan 1

Affiliation(s)

1 College of Science, Xi'an Polytechnic University, Xi'an, Shanxi, 710600, China

Corresponding Author

Rongguo Qu

ABSTRACT

The flower pollination algorithm exhibits notable strengths, including robust search capabilities, minimal parameter requirements, and a straightforward architecture, but due to the randomness of its local search, it leads to slow convergence. Comparatively, the raccoon optimization algorithm does not require parameter adjustment, and the local search range is gradually reduced over time, ensuring the algorithm's effectiveness and convergence. However, for solving high-dimensional complex problems, the global search time is too long to reach the optimal global solution. Therefore, This study introduces a novel coati flower pollination algorithm incorporating an intra-group competition mechanism, effectively integrating the global exploration capabilities of FPA with the local exploitation characteristics of COA. The algorithm divides the population by k-means clustering to improve diversity and utilizes the competition mechanism to promote information exchange among individuals. For winning and losing individuals, the improved flower pollination algorithm and coati optimization algorithm are used for iterative updating, respectively, and adaptive polynomial mutation is introduced to avoid local optima. The superiority of the algorithm is verified on the CEC2017.

KEYWORDS

Flower Pollination Algorithm, Coati Optimization Algorithm, K-means Clustering Method, Competition Mechanism, Polynomial Mutation

CITE THIS PAPER

Rongguo Qu, Zhenxing Yu, Dewei Yang, Jin Su, Qinwei Fan, A Nature-inspired Fully Enhanced Hybrid Algorithm Based on Intra-group Competition Mechanism. Journal of Network Computing and Applications (2025) Vol. 10: 49-62. DOI: http://dx.doi.org/10.23977/jnca.2025.100107.

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