Abstract:To solve the problems of glowworm swarm optimization (GSO) algorithm in low computational accuracys,low convergence speed,and easy to fall into local optimizaiton,the chaos algorithm and cloud model algorithm were introduced to optimize the evolution mechanism of GSO and chaos cloud model glowworm swarm optimization (CCMGSO) algorithm was proposed.In the evolutionary process,the cloud model algorithm and excellent glowworms were applied to local excavation refinement,to increase the accuracy of solution,meanwhile the chaos algorithm and ordinary glowworms were used to exploration of global optimization,to avoid falling into local optimal.Through the functions testing,experiment results show that the proposed algorithm is superior to GSO and GSO based on max-min luciferin in computational accuracys,covergence speed and find the global optimum.