An Improved Coati Optimization Algorithm Based on Multi-Strategy

Abstract

To solve the problems of the original Coati Optimization Algorithm with low exploration ability, insufficient exploitation ability and easy to fall into local optimum, an improved coati optimization algorithm based multi-strategy is proposed. Firstly, the initial solution traversal is improved through Circle chaotic mapping to lay the foundation for global search; secondly, the local optimum is jumped out through Lévy flight to improve the global search ability of the algorithm; finally, the performance of the proposed algorithm is evaluated using numerical analysis and convergence analysis in comparison with four algorithms such as PSO and WOA. The experimental results show that the algorithm in this paper has better search accuracy and convergence speed and has better performance in solving high-dimensional problems.