基于标准萤火虫算法的改进与仿真应用

通过对一种智能优化算法——萤火虫算法的研究,在标准萤火虫算法中引入一种新型的自适应惯性权重来提高算法的收敛速度,并提出用虚拟萤火虫来加强萤火虫之间的相互协作和信息共享,进而改进了萤火虫的位置更新公式。针对算法中萤火虫位置的越界问题和边界早熟问题,引入一种对称边界变异,提高了改进后的算法的寻优率。对6个标准测试函数的实验结果表明:改进后的萤火虫算法的有效性、收敛速度得到了明显的提高。最后对两个经典工程优化问题进行了计算,运用改进后的算法所得的结果优于其它算法所得结果,也验证了萤火虫算法在改进后的适用性。

Improvement and Simulation Application Based on Standard Firefly Algorithm

Through studying a kind of intelligent optimization algorithm namely firefly algorithm,the standard updating formula of firefly algorithm is improved by introducing the new adaptive inertia weight to increase the convergence speed of the algorithm and the virtual firefly is used to enhance the cooperation and the exchange of information between the fireflies.For the firefly algorithm in cross-border issues and early boundary problem,a symmetric boundary mutation is introduced,so as to improve the optimization rate of algorithm.The experiment results of six standard test functions show that the effectiveness and the convergence speed of the improved firefly algorithm are improved.In the end,the algorithm is applied to two classical engineering optimization problems,the superiority of the improved firefly algorithm is confirmed by the experiment results,and the applicability of the improved firefly algorithm is verified.