基于混沌和非线性规划的萤火虫算法

Firefly Algorithm Based on Chaos and Nonlinear Programming

为了弥补标准萤火虫算法(FA)收敛性差、精度低和时间性能差等不足,采用Tent混沌映射初始化萤火虫种群位置,提升初始化萤火虫种群质量;在萤火虫位置更新迭代过程中,采用非线性规划优化萤火虫位置,增强了算法的局部搜索能力,提高了算法的收敛性能和优化精度以及时间性能。通过仿真证明所提出的新算法具有较强的搜索能力和收敛性,提高了标准萤火虫算法的求解精度。

To make up the lack of poor convergence,low accuracy and poor performance of the standardfirefly algorithm(FA),to initialize the firefly population position by using Tent chaotic mapping,thequality of the population initialization firefly was enhanced;to update the firefly position by the nonlinearoptimization in the iterative process,the local search ability of the algorithm was enhanced,A fireflyalgorithm based on chaos and nonlinear programming(TNFA)is proposed and improves the convergenceperformance and optimization accuracy and the time performance.The simulation shows that theproposed algorithm has strong search ability and convergence,improve the accuracy of standard fireflyalgorithm.