Competitive group optimization method based on multiple strategies and two stages

The invention relates to the technical field of information, and discloses a multi-strategy two-stage-based competitive group optimization method, which meets execution conditions of a first stage of an algorithm, executes a fuzzy search strategy on a loser particle, executes a self-adaptive two-way sampling strategy on a winner particle, learns the loser particle and a sampling particle thereof towards the winner particle, and obtains a first stage of the algorithm, a second stage of the algorithm and a third stage of the algorithm. And if the execution condition of the second stage of the algorithm is satisfied, the loser particle performs enhanced convergence learning on the winner particle. According to the competition group optimization method based on the multiple strategies and the two stages, the purpose of efficiently searching the whole space is achieved through the first evolution stage, and in the stage, the whole space can be more efficiently searched through the algorithm under the assistance of