Computer Engineering and Applications ›› 2019, Vol. 55 ›› Issue (7): 1-8.DOI: 10.3778/j.issn.1002-8331.1812-0263

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Firefly Algorithm Based on Topology Improvement and Crossover Strategy

ZHANG Zhechen,LIU Sanyang   

  1. College of Mathematics and Statistics, Xidian University, Xi’an 710071, China
  • Online:2019-04-01 Published:2019-04-15



  1. 西安电子科技大学 数学与统计学院,西安 710071

Abstract: Aiming at the problems of Firefly Algorithm(FA), such as high complexity, difficulty in optimizing high-dimensional function and easily to fall into local minimum, a new algorithm based on topology improvement and crossover strategy is proposed. The algorithm uses von Neumann topology structure to simulate the neighborhood structure between fireflies, which strengthens the global search ability and reduces the computational complexity. At the same time, adaptive crossover strategy is introduced in this algorithm. The crossover probability is adjusted dynamically according to the diversity of fireflies, which enhances the ability of fireflies to jump out of the local optimum. The simulation results of eight standard test functions indicate that the improved firefly algorithm has higher convergence accuracy and stability than the standard firefly algorithm.

Key words: Firefly Algorithm(FA), neighborhood structure, von Neumann structure, adaptive crossover strategy

摘要: 针对萤火虫算法(FA)复杂度大,对高维函数优化困难,容易陷入局部极小值等问题,提出了基于拓扑改进与交叉策略的萤火虫算法。该算法用冯诺依曼拓扑结构来模拟萤火虫之间的邻域结构,提高了全局搜索能力,并且减小了计算复杂度。同时,引入自适应交叉策略,根据萤火虫的多样性动态的调整交叉概率,增强了萤火虫跳出局部最优的能力。对8个标准测试函数的仿真实验表明,改进后的萤火虫算法与标准萤火虫算法相比,有更高的收敛精度和稳定性。

关键词: 萤火虫算法, 邻域结构, 冯诺依曼结构, 自适应交叉策略