To solve the problems that whale optimization algorithm is easy to fall into local optimization and slow convergence speed, and the improved whale optimization algorithm is proposed. Firstly, the algorithm uses Skew Tent chaotic map to initialize the whale population, improve the diversity of the original whale population and make the individual position distribution of whales more uniform; Secondly, the nonlinear convergence factor based on inverse incomplete Γ function is used to balance the global exploration and local development ability of whale algorithm. Through the simulation experiments of 8 benchmark functions, from the perspective of mean square deviation and average value, the convergence speed and optimization accuracy of the improved whale optimization algorithm are significantly higher than those of the traditional whale optimization algorithm.

Peng Gao, Hangqi Ding, Rui Xu. Whale Optimization Algorithm Based on Skew Tent Chaotic Map and Nonlinear Strategy. Academic Journal of Computing & Information Science (2021), Vol. 4, Issue 5: 91-97. https://doi.org/10.25236/AJCIS.2021.040513.

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