计算机科学 ›› 2017, Vol. 44 ›› Issue (5): 257-262.doi: 10.11896/j.issn.1002-137X.2017.05.046
韩守飞,李席广,拱长青
HAN Shou-fei, LI Xi-guang and GONG Chang-qing
摘要: 烟花算法(Fireworks Algorithm,FWA)是一种群体智能优化算法,具有求解复杂问题的全局最优解的能力。为了提高FWA求解全局最优解的能力,将模拟退火的思想引入到烟花优化算法中,并对FWA中某些单个烟花个体进行高斯扰动,提出了一种基于模拟退火与高斯扰动的烟花优化算法(SAFWA)。分别把烟花算法(FWA)、标准粒子群算法(SPSO)、增强烟花算法(EFWA)和SAFWA在10个典型的基准测试函数中进行仿真对比,结果表明,在收敛速度、计算精度以及稳定性方面,SAFWA均优于其他3种算法。
[1] TAN Y,ZHENG S Q.Recent advances in fireworks algorithm[J].CAAI Transactions on Intelligent Systems,2014,9(5):515-528.(in Chinese) 谭营,郑少秋.烟花算法研究进展[J].智能系统学报,2014,9(5):515-528. [2] ZHENG S,JANECEK A,TAN Y.Enhanced fireworks algo-rithm[C]∥2013 IEEE Congress on Evolutionary Computation (CEC).2013. [3] ZHENG Y J,XU X L,LING H F,et al.A hybird fireworks optimization method with differential evolution operators[J].Nenurocomputing,2015,148:75-80. [4] YU C,KELLEY L,ZHENG S,et al.Fireworks algorithm with differential mutation for solving the CEC 2014 Competition problems[C]∥2014 IEEE Congress on Evolutionary Computation.2014:3238-3245. [5] GAO H,DIAO M.Cultural fireworks algorithm and its Application for digital filters design[J].International Journal of Modelling,Identification and Control,2011,4(4):324-331. [6] ZHANG B,ZHANG M X,ZHENG Y J.A hybird bi-Geography-based optimization and fireworks algorithm[C]∥2014 IEEE Congress on Evolutionary Computation.2014:3200-3206. [7] TAN Y,YU C,ZHENG S,et al.Introduction to fireworks algorithm[J].International Journal of Swarm Intelligence Research,2013,4(4):39-70. [8] TAN Y,ZHU Y.Fireworks algorithm for optimization[M].Berlin Springer,2010:355-364. [9] ZHOU Y,TAN Y.GPU-based parallel particle swarm optimiza-tion[C]∥IEEE Congress on Evolutionary Computation.2009:1493-1500. [10] LIU J,ZHENG S,TAN Y.Analysis on global convergence and time complexity of fireworks algorithm[C]∥2014 IEEE Congress on Evolutionary Computation(CEC).Beijing,China,2014:3207-3213. [11] CHEN H G,WU J S,WANG J L.Mechanism study of simulated annealing algorithm[J].Journal of Tongji University(Natural Science),2004,2(6):802-806.(in Chinese) 陈华根,吴建生,王家林.模拟退火算法机理研究[J].同济大学学报(自然科学版),2004,2(6):802-806. [12] HE X S,DING W J,YANG X S.Bat algorithm based on simulated annealing and Gaussian perturbations[J].Application Research of Computers,2014,1(2):392-397.(in Chinese) 贺兴时,丁文静,杨新社.基于模拟退火高斯扰动的蝙蝠优化算法[J].计算机应用研究,2014,1(2):392-397. [13] ZHANG Y,HE X S,YANG X S.A cuckoo search algorithmbased on simulated annealing and Gaussian disturbance [J].BasicSciences Journal of Textfile Universites,2015,28(4):515-521.(in Chinese) 张毅,贺兴时,杨新社.基于模拟退火高斯扰动的布谷鸟算法[J].纺织高校基础科学学报,2015,8(4):515-521. [14] 谭营.烟花算法引论[M].北京:科学出版社,2015. [15] 藤素珍,冯敬海.数理统计学[M].大连:大连理工大学出版社,2005. [16] BRATTON D,KENNEDY J.Defining a standard for particle swarm optimization[C]∥Swarm Intelligence Symposium.2007. |
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