Chaotic glowworm swarm optimization algorithm based on Gauss mutation

Abstract

Aiming at the shortcoming of solving the optimal value in basic glowworm swarm optimization (GSO) algorithm, the paper proposes a chaotic GSO algorithm based on Gauss mutation (GMCGSO). GMCGSO uses Gauss mutation strategy in the process of glowworm moving, which prevents the algorithm from falling into local optima to some extent, and obtains much higher precision solution by taking use of the ergodicity of chaotic operator. Through the simulation of eight standard test functions we can see that the improved artificial glowworm swarm optimization algorithm has much higher convergence speed, computing precision and the success rate of convergence in comparison with the other algorithms.