Abstract: Glowworm Swarm Optimization（GSO） algorithm is a novel search algorithm which simulates the social behavior of glowworm swarm in the nature depending on fluorescein communication. Based on the analysis of shortcomings of basic GSO such as lack and lag of collaboration among glowworm. This paper proposes a new GSO which is more close to natural glowworm swarm system. By setting up the fluorescein diffusion model, this algorithm improves the collaboration among glowworms which are nearby. The simulation results show that the GSO based on fluorescein diffusion has greatly improved than the basic algorithm in terms of overall and convergence.

Key words: Glowworm Swarm Optimization, fluorescein, diffusion mechanism

摘要： 人工萤火虫算法是一种新型的搜索算法，其模拟自然界萤火虫利用荧光素进行联系而表现出的社会性行为。在基本萤火虫算法中，萤火虫之间存在协作不足，易陷入局部最优的缺陷。提出了一种新的更接近自然界萤火虫信息交流系统的萤火虫算法。该算法通过建立荧光素扩散模型，使相距较近的萤火虫之间能更好地进行协作。数值仿真实验结果表明，基于荧光素扩散的萤火虫算法，在全局性和收敛性方面比基本萤火虫算法有显著的提高。

关键词: 萤火虫算法, 荧光素, 扩散机制