An optimized bat algorithm based on particle swarm optimization
To solve the inefficient search problems of the traditional bat algorithm in the later part of optimization process,such as poor optimization, serious deviation, easily falling into local optimal solution,an optimized bat algorithm based on particle swarm algorithm is proposed for optimizing local search process.The presented algorithm can produce some alternative best-bat operators in local search process,which competes against the other bat operators,produced by the traditional bat algorithm,and then enrich the diversity of the operator population and improve searching ability. The simulation under Matlab environment show that the improved algorithm(PSOBA)can improve the convergence speed and precision obviously,and has higher processing dimension,thus provides an effective method to solve the problem of complex function optimization.
bat algorithmparticle swarm algorithmcompetitive mechanismfunction optimiza-tionlocal area deep-searching convergence speed
NETL
NSTL
万方数据
维普
