Multistrategy Harris Hawks Optimization Algorithm Using Chaotic Method, Cauchy Mutation, and Elite Individual Guidance

Aiming at the shortcomings of Harris hawks optimization algorithm (HHO), such as poor initial population diversity, slow convergence speed, local ability, and easily falling into optimum, a (CCCHHO) integrating multiple mechanisms is proposed. First, diversity enhanced by initialization chaotic method. Second, cosine function used to better simulate characteristics periodic change energy prey in repeated contests with group hawks, balance exploration exploitation algorithm. Third, Cauchy mutation on optimal individual phase performed, distribution enhance are used, which can effectively prevent from optimum. Fourth, ability using ergodicity system perform search for enhanced, jump out after falls Finally, we use elite individuals guide position update population’s individuals, fully communicate dominant speed up Through simulation experiments CCCHHO 11 different benchmark functions, than gray wolf (GWO), Salp swarm (SSA), ant lion (ALO), three improved HHO algorithms terms accuracy, whether it unimodal or multimodal function. The experimental results show that has excellent efficiency robustness.