The Whale Optimization Algorithm(WOA)is a novel swarm intelligence optimization al-gorithm that converges based on probability.It features simple and easily implementable algorithm prin-ciples,a small number of easily adjustable parameters,and a balance between global and local search control.This paper systematically analyzes the basic principles of WOA and factors influencing algo-rithm performance.It focuses on discussing the advantages and limitations of existing algorithm im-provement strategies and hybrid strategies.Additionally,the paper elaborates on the applications and developments of WOA in support vector machines,artificial neural networks,combinatorial optimiza-tion,complex function optimization,and other areas.Finally,considering the characteristics of WOA and its research achievements in applications,the paper provides a prospective outlook on the research and development directions of WOA.
维普
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