Improved Glowworm Swarm Optimization Based on the Behavior of Follow
基于追尾行为的改进型人工萤火虫群算法

To improve the glowworm swarm optimization, the behavior of follow of the artificial fish school algorithm and a swarm degree were used. The improved algorithm was used to optimise multi modal functions. The experiment resups show that the algorithm, with the smaller populations and the fewer number of iterations, can simultaneous capture multiple optima of several standard multimodal test function.