The Particle Swarm Optimization Algorithm of Research based on Genetic Algorithm

摘要

Aiming at the complex particle swarm algorithm of the multi-model optimizing easily into the local extremum and search for the problem of low efficiency,puts forward a new hybrid particle swarm algorithm,namely GA-PSO genetic algorithm and particle swarm algorithm combining with genetic algorithm big range search ability and inherent parallelism,combining particle swarm algorithm few parameters,operation simple features,strengthening the particle swarm the global search ability,improves the convergence of the effect of particle swarm,through continuous complex the multi-model simulation shows the effectiveness of the proposed algorithm and feasibility,especially for has many local extreme value point of complex the multimodel global optimization,this algorithm can accurately effectively find global optimal value.