An Improved Optimization Algorithm Based on Leapfrog and Whale Optimization Fusion

Abstract

Whale optimization algorithm is a new type of swarm intelligence optimization algorithm. Aiming at the problems of low optimization accuracy and easy falling into local optima in the basic whale optimization algorithm, an improved whale optimization algorithm that combines the whale algorithm and the hybrid leapfrog search strategy is proposed. The local search mechanism of the hybrid frog leaping algorithm is used to update the position of the whale to improve the accuracy of convergence; when the individual position of the population is updated, an attenuation factor is introduced to disturb the update position of the individual whale, thereby increasing the diversity of the population and adjusting the search scale of the algorithm . Simulation experiment results show that the overall optimization performance of the improved algorithm is better than the original whale algorithm, particle swarm and gray wolf optimization algorithm.