When resolving complex problems, the particle swarm optimization(PSO) has some disadvantages of slow
convergence rate and easiness to fall into local optimal solution. Therefore, a particle swarm optimization with the
deindividuation theory(DTPSO) is proposed. Based on the social identity model of deindividuation effects, the diversity
and effectiveness of population can be maintained through the deindividuation acts, the balance between individuality and
convergence) of individual particles during their evolution process. The results of simulation experiment show that the
DTPSO possesses higher convergence rate and convergence precision, as well as better stability.