SWOA: whale optimization algorithm incorporating simplex reinforcement

In recent years, the improved whale optimization algorithm has been widely used in optimization problems, but there are still defects such as the lack of information exchange between populations and the tendency to fall into the local optimum, etc. In order to solve the above problems, a whale optimization algorithm incorporating simplex reinforcement (Whale optimization algorithm based on simplex method, SWOA) is proposed. Firstly, one-dimensional composite chaotic mapping SPM strategy is introduced to increase the initialized whale population diversity and improve the global optimization ability of the WOA algorithm. Secondly, the simplex method is combined with the simplex method to optimize the individual whales in the iterative process through reflection, expansion and compression operations, which improves the local searching and optimization ability of the algorithm. Comparative analyses of the optimization search results of eight benchmark functions in cec2005 are carried out, and the results show that the improved SWOA has better convergence accuracy and stability.