Abstract
The loser-out tournament-based firework algorithm (LoTFWA) is a new baseline among firework algorithm (FWA) variants due to its outstanding performance in multimodal optimization problems. LoTFWA successfully achieves information-interaction among populations by introducing a competition mechanism, while information-interaction within each sub-population remains insufficient. To solve this issue, this paper proposes a micro-population evolution strategy and a hybrid algorithm LoTFWA-microDE. Under the proposed strategy, sparks generated by one firework make up a micro-population which is taken into the differential evolution procedure. The proposed algorithm is tested on the CEC’13 benchmark functions. Experimental results show that the proposed algorithm attains significantly better performance than LoTFWA and DE in multimodal functions, which indicates the superiority of the proposed micro-population evolution strategy.
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Acknowledgements
This work is supported by Beijing Natural Science Foundation (1202020), National Natural Science Foundation of China (61973042) and BUPT innovation and entrepreneurship support program (2022-YC-A287). Awfully thanks will be given to Swarm Intelligence Research Team of BeiYou University.
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Han, M., Fan, M., Han, N., Zhao, X. (2022). A Micro-population Evolution Strategy for Loser-Out Tournament-Based Firework Algorithm. In: Tan, Y., Shi, Y., Niu, B. (eds) Advances in Swarm Intelligence. ICSI 2022. Lecture Notes in Computer Science, vol 13344. Springer, Cham. https://doi.org/10.1007/978-3-031-09677-8_27
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