Artificial glowworm swarm optimization algorithm with Gauss mutation
带高斯变异的人工萤火虫优化算法

According to the basic glowworm swarm optimization algorithm problems in solving the function of global optimal value, the paper put forward an artificial glowworm swarm optimization algorithm with Gauss mutation. The algorithm used a Gauss mutation strategy in the firefly mobile process, to prevent the algorithm into a local optimum in a certain extent, and obtained a more accurate solution. Finally, the test results of six standard test functions show that, the improved algorithm has higher convergence speed, solution precision and convergence rate of success than the basic GSO algorithm.