Abstract
This paper improves the Artificial Hummingbird Algorithm (AHA). First, we introduce a compact scheme to reduce computer storage capacity and speed up computation. Second, the parallel strategy is added to improve the optimization ability of the algorithm. Third, we improve the original algorithm’s territorial and migration foraging strategies. The purpose of enhancing the territorial foraging strategy is to optimize the algorithm to be more directional. We removed the migration-foraging strategy, which is more suitable for combining with the compact scheme. Finally, we tested the improved algorithm on the cec2013 test set, which showed good performance.
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Chu, SC., Shao, ZY., Shieh, CS., Zhang, X. (2023). Artificial Hummingbird Algorithm with Parallel Compact Strategy. In: Ni, S., Wu, TY., Geng, J., Chu, SC., Tsihrintzis, G.A. (eds) Advances in Smart Vehicular Technology, Transportation, Communication and Applications. Smart Innovation, Systems and Technologies, vol 347. Springer, Singapore. https://doi.org/10.1007/978-981-99-0848-6_27
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DOI: https://doi.org/10.1007/978-981-99-0848-6_27
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