Salp Swarm Algorithm Nad Application Research

The Salp Swarm algorithm(SSA)is a new intelligent group optimization algorithm for simulating the movement and predation behavior of biological sea otters in the ocean.The algorithm has the characteristics of simple structure,strong search ability,strong robustness and easy implementation.However,with the deepening of the research,the researchers found that the Salp optimization algorithm also has the shortcomings of low optimization accuracy and easy to fall into local optimum.In this thesis,the deficiencies of Salp optimization algorithm are improved,and the improved algorithm is applied to the optimization problem.The purpose is to improve the theoretical basis of Salp optimization algorithm and expand its application range.The main research work of this thesis includes:(1)The simplex method is used to improve the plant sea otter optimization algorithm,which increases the global and local search ability of the algorithm,avoids the algorithm falling into local optimum in the later stage,and improves the convergence speed of the algorithm,making the overall performance of the salp optimization algorithm more excellent.(2)In order to increase the diversity of the optimization algorithm population,polar coordinate coding is applied to the optimization algorithm of the sea bottle,and an optimization algorithm of sea bottle based on polar coordinate coding is proposed.Compared with the traditional real number coding,polar coordinate coding enlarges the diversity and search space of individuals,reduces the possibility of falling into local optimum,and effectively improves the convergence and stability of the algorithm,thus avoiding the situation of individuals falling into local optimum when searching.Experiments show that the polar coordinate coding algorithm has certain advantages in solving some complex optimization problems.