差分进化引导趋化算子的烟花优化算法
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摘要
标准烟花算法粒子间交流机制存在缺陷,且对最优点位置不在原点和原点附近时的目标函数求解能力差,对此提出差分进化引导趋化算子的烟花算法(BFA)。利用差分进化算法和趋化算子的局部搜索优势,在每一次迭代的过程中不断寻找这一代的最好个体,通过最优个体信息对局部粒子维度信息进行修改从而使得整个群体得到改善,8个标准和增加位置偏移的测试函数仿真结果表明,BFW相比于原始烟花算法(FA),粒子群算法和SPSO在寻优精度和寻优速度上有了较好的提高。
In order to solve the default of the fireworks algorithm inter-particle exchange mechanism and the disadvantage that the optimal position is not solved by the objective function near the origin and the origin come up with fireworks algorithm optimization with chemotaxis operator(BFW). Using the local search advantage of the chemotaxis operator to find the best individual in every iteration to improve the whole population's search ability. The improved algorithm has been tested on 8 benchmark functions. The experimental results show that BFW has better behaviors in convergence accuracy and speed.
In order to solve the default of the fireworks algorithm inter-particle exchange mechanism and the disadvantage that the optimal position is not solved by the objective function near the origin and the origin come up with fireworks algorithm optimization with chemotaxis operator(BFW). Using the local search advantage of the chemotaxis operator to find the best individual in every iteration to improve the whole population's search ability. The improved algorithm has been tested on 8 benchmark functions. The experimental results show that BFW has better behaviors in convergence accuracy and speed.
引文
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[2] Gao H,Diao M.Cultural firework algorithm and its application for digital filters design[J].International Journal of Modelling,Identification and Control,2011,14(4):324-331.
[3] Li J,Zheng S,Tan Y.The effect of information utilization:introducing a novel guiding spark in the fireworks algorithm[J].IEEE Transactions on Evolutionary Computation,2017,21(1):153-166.
[4]曹炬,李婷婷,贾红.带有遗传算子的烟花爆炸优化算法[J].计算机工程,2010,36(23):149-151.
[5] Guendouz M,Amine A,Hamou R M.A discrete modified fireworks algorithm for community detection in complex networks[J].Applied Intelligence,2017,46(2):373-385.
[6] Fang Liuping,Wang Jiwen,Qiu Jianfeng,et al,Dynamic search firework algorithm with learning factor[J].Journal of Frontiers of Computer Science and Technology,2017,11(3):491-501.
[7] Rashedi E,Nezamabadi H,Saryazdi S.GSA:a gravitational search algorithm[J].Information Science,2009,179(13):2232-2248.
[8] Zhou Yalan.Research and application on bacteria foraging optimization algorithm[J].Computer Engineering and Applications,2010,46(20):16-21.
[9] Kim D H,Abraham A.A hybrid genetic algorithm and acterial foraging approach for global optimization and robust tuning of PID controller with disturbance rejection[J].Studies in Computational Intelligence,2007,75:171-199.
[10] Rashedi E,Nezamabadi H,Saryazdi S.GSA:a gravitational search algorithm[J].Information Science,2009,179(13):2232-2248.
[11]包晓晓,叶春明,黄霞.烟花算法求解JSP问题的研究[J].计算机工程与应用,2017,53(3):247-252.
[12]姜道银,葛洪伟,袁罗.一种动态划分的混合连续域蚁群优化算法[J].计算机工程与应用,2018,54(7):144-151.
[13] Li C,Zhou J.Parameters identification of hydraulic turbine governing system using improved gravitational search algorithm[J].Energy Conversion and Management,2011,52(1):374-381.
[14] Zhao X.A perturbed particle swarm algorithm for numerical optimization[J].Applied Soft Computing,2010,10(1):119-124.
[15] Coello C A.Evolutionary multi-objective optimization:a historical view of the field[J].IEEE Computational Intelligence Magazine,2006,1(1):28-36.
[16]谢晓锋,张文俊,张国瑞,等.差异演化的实验研究[J].控制与决策,2004,19(1):49-52.
[17] Wang Ling,Pan Quanke,Suganthan P N,et al.A novel hybrid discrete differential evolution algorithm for blocking flow shop scheduling problems[J].Computers and Operations Research,2010,37(3):509-520.