Whaleoptimization Algorithm Based on Adaptive Weight and Cauchy Mutation

In order to improve the problem that the whale algorithm (WOA) is easy to fall into the local optimum and the convergence accuracy is low, a whale algorithm based on adaptive weight and Cauchy mutation is proposed (WOAWC). Firstly, the variation of the whale's position is modified by the Cauchy inverse cumulative distribution function method, which improves the global search ability of the whale algorithm and avoids the local optimization. In addition, the local search ability of the whale algorithm is improved by the adaptive weighting method, and the convergence accuracy is improved. The experimental results show that the improved algorithm is superior to the original whale algorithm, genetic algorithm and particle swarm optimization, Convergence accuracy and algorithm stability are better than other algorithms.