A Fusion Crossover Mutation Sparrow Search Algorithm

Aiming at the inherent problems of swarm intelligence algorithm, such as falling into local extremum in early stage and low precision later stage, this paper proposes an improved sparrow search algorithm (ISSA). Firstly, we introduce idea flight behavior bird SSA to keep diversity population reduce probability optimum; Secondly, creatively crossover mutation genetic get better next-generation population. These two improvements not only all times but also make up for defect that is easy fall optimum end iteration. The optimization ability greatly improved.