Abstract: Aiming at the performance comparison of swarm intelligence optimization algorithms that lacks qualified research findings,we constructed a platform for comparing the performance of the algorithms.Then,we proposed the novel performance evaluation criteria for convergence relational degree and the convergence area based on the changes of the best individual.Specifically,we compared and tested the performances of several swarm intelligence optimization algorithms,such as the genetic algorithm (GA),particle swarm optimization (PSO) algorithm,artificial fish swarm (AFS) algorithm,bacterial foraging (BF) algorithm and artificial bee colony (ABC) algorithm.Experimental results showed that the platform and criteria of performance evaluation proposed in this paper can be effectively used to compare the capability of optimization search under different mechanisms.