具有自适应步长与协同寻优的蝙蝠烟花混合算法
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摘要
论文提出了一种新的群体智能优化算法——蝙蝠烟花混合算法.该算法采用蝙蝠算法在全局最优附近的位置信息、蝙蝠发出的频率、全局最优以及烟花的位置信息构造了新的爆炸半径,使烟花算法在寻优的过程中能够自动地调整步长;并且使蝙蝠个体与烟花个体实现协同寻优;最后,采用"精英-随机"策略选择下一代烟花,增加了烟花种群的多样性.与其他算法(如蝙蝠算法、标准粒子群算法、烟花算法等)相比,函数优化问题以及0-1背包问题的对比实验结果表明:论文提出的混合算法的整体性能优于其他五种算法.
This paper proposes a new swarm intelligent optimization algorithm called hybrid Bat and Fireworks algorithm. This hybrid algorithm adopts the position information around the global optimum,the frequency of the bat particle,the global best particle and the fireworks particle's location information to construct a new explosion radius,so that the fireworks algorithm can adjust the step size automatically during the optimization process,and make the individual bat and the individual fireworks achieve cooperatrive optimization.Finally,adopting the Elite-Random strategy to select the next generation of fireworks,which can increase diversity of fireworks populations. Comparing with other algorithms,such as bat algorithm,standard particle swarm algorithm,fireworks algorithm and so on,the experimental results of function optimization problems and 0-1 knapsack problems show that the hybrid algorithm proposed in this paper outperforms the other five algorithms.
This paper proposes a new swarm intelligent optimization algorithm called hybrid Bat and Fireworks algorithm. This hybrid algorithm adopts the position information around the global optimum,the frequency of the bat particle,the global best particle and the fireworks particle's location information to construct a new explosion radius,so that the fireworks algorithm can adjust the step size automatically during the optimization process,and make the individual bat and the individual fireworks achieve cooperatrive optimization.Finally,adopting the Elite-Random strategy to select the next generation of fireworks,which can increase diversity of fireworks populations. Comparing with other algorithms,such as bat algorithm,standard particle swarm algorithm,fireworks algorithm and so on,the experimental results of function optimization problems and 0-1 knapsack problems show that the hybrid algorithm proposed in this paper outperforms the other five algorithms.
引文
[1]Tan Y,Zhu Y.Fireworks algorithm for optimization[C]//International Conference on Advances in Swarm Intelligence,SpringerVerlag,2010:355-364
[2]Bao Xiao-xiao,Ye Chun-ming,Huang Xia.Solving job-shop scheduling problem by firework algorithm[J].Computer Engineering and Applications,2017,53(3):247-252.
[3]Fan Hong,Hou Cun-cun,Zhu Yan-chun,et al.Soft subspace algorithm for MR image clustering based on fireworks optimization algorithm[J].Joumal of Software,2017,28(11):3080-3093.
[4]Yang Zhi-sheng,Zhu Can-shi,Gao Yang-jun.Enhanced fireworks algorithm for RFID network planning[J].Computer Engineering and Applications,2017,53(3):23-27.
[5]Tuba E,Tuba M,Dolicanin E.Adjusted fireworks algorithm applied to retinal image registration[J].Studies in Informatics&Control,2017,26(1):33-42.
[6]Li J,Tan Y.Loser-out tournament based fireworks algorithm for multi-modal function optimization[J].IEEE Transactions on Evolutionary Computation,2017,(99):1-1.
[7]Tan Ying,Zheng Shao-qiu.Recent advances in fireworks algorithm[J].CAAI Transactions on Intelligent Systems,2014,9(5):515-528.
[8]Liu J,Zheng S,Tan Y.The improvement on controlling exploration and exploitation of firework algorithm[M].Advances in Swarm Intelligence,Springer Berlin Heidelberg,2013:11-23.
[9]Zheng S,Janecek A,Tan Y.Enhanced fireworks algorithm[C]//IEEE Congress on Evolutionary Computation,Cancun,Mexico,2013:2069-2077.
[10]Zheng S,Janecek A,Li J,et al.Dynamic search in fireworks algorithm[C]//Evolutionary Computation,IEEE,2014:3222-3229.
[11]Li J,Zheng S,Tan Y.Adaptive fireworks algorithm[C]//IEEECongress on Evolutionary Computation(CEC),Beijing,2014:3214-3221.
[12]Li Xi-guang,Han Shou-fei,Liu Xiao-jing,et a1.Fireworks algorithm based on reverse learning and dynamic memory feedback[J].Computer Engineering,2017,43(12):203-210.
[13]Li J,Zheng S,Tan Y.The effect of information utilization:introducing a novel guiding spark in the fireworks algorithm[J].IEEETransactions on Evolutionary Computation,2017,21(1):153-166.
[14]Fang Liu-ping,Wang Ji-wen,Qiu Jian-feng,et al.Dynamic search fireworks algorithm with learning factor[J].Journal of Frontiers of Computer Science and Technology,2017,11(3):491-501.
[15]Gao H,Diao M.Cultural firework algorithm and its application For digital filters design[J].International Journal of Modelling Identification&Control,2011,14(4):324-331.
[16]Yu C,Kelley L,Zheng S,et al.Fireworks algorithm with differential mutation for solving the CEC 2014 competition problems[C]//Evolutionary Computation,IEEE,2014:3238-3245.
[17]Zhang B,Zhang M X,Zheng Y J.A hybrid biogeography-based optimization and fireworks algorithm[C]//Evolutionary Computation,IEEE,2014:3200-3206.
[18]Yang X S.A new metaheuristic bat-inspired algorithm[J].Computer Knowledge&Technology,2010,284:65-74.
[19]Kennedy J,Eberhart R.Particle swarm optimization[C]//IEEEInternational Conference on Neural Networks,2002:1942-1948.
[20]Shi Y,Eberhart R.A modified particle swarm optimizer[C]//IEEE International Conference on Evolutionary Computation Proceedings,Xplore,1999:69-73.
[21]Zou D,Gao L,Li S,et al.Solving 0-1 knapsack problem by a novel global harmony search algorithm[J].Applied Soft Computing,2011,11(2):1556-1564.
[2]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.
[3]范虹,侯存存,朱艳春,等.烟花算法优化的软子空间MR图像聚类算法[J].软件学报,2017,28(11):3080-3093.
[4]杨志升,朱参世,高杨军.利用增强烟花算法对RFID网络进行规划[J].计算机工程与应用,2017,53(3):23-27.
[7]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.
[12]李席广,韩守飞,刘晓静,等.基于反向学习与动态记忆反馈的烟花算法[J].计算机工程,2017,43(12):203-210.
[14]方柳平,汪继文,邱剑锋,等.具有学习因子的动态搜索烟花算法[J].计算机科学与探索,2017,11(3):491-501.
[2]Bao Xiao-xiao,Ye Chun-ming,Huang Xia.Solving job-shop scheduling problem by firework algorithm[J].Computer Engineering and Applications,2017,53(3):247-252.
[3]Fan Hong,Hou Cun-cun,Zhu Yan-chun,et al.Soft subspace algorithm for MR image clustering based on fireworks optimization algorithm[J].Joumal of Software,2017,28(11):3080-3093.
[4]Yang Zhi-sheng,Zhu Can-shi,Gao Yang-jun.Enhanced fireworks algorithm for RFID network planning[J].Computer Engineering and Applications,2017,53(3):23-27.
[5]Tuba E,Tuba M,Dolicanin E.Adjusted fireworks algorithm applied to retinal image registration[J].Studies in Informatics&Control,2017,26(1):33-42.
[6]Li J,Tan Y.Loser-out tournament based fireworks algorithm for multi-modal function optimization[J].IEEE Transactions on Evolutionary Computation,2017,(99):1-1.
[7]Tan Ying,Zheng Shao-qiu.Recent advances in fireworks algorithm[J].CAAI Transactions on Intelligent Systems,2014,9(5):515-528.
[8]Liu J,Zheng S,Tan Y.The improvement on controlling exploration and exploitation of firework algorithm[M].Advances in Swarm Intelligence,Springer Berlin Heidelberg,2013:11-23.
[9]Zheng S,Janecek A,Tan Y.Enhanced fireworks algorithm[C]//IEEE Congress on Evolutionary Computation,Cancun,Mexico,2013:2069-2077.
[10]Zheng S,Janecek A,Li J,et al.Dynamic search in fireworks algorithm[C]//Evolutionary Computation,IEEE,2014:3222-3229.
[11]Li J,Zheng S,Tan Y.Adaptive fireworks algorithm[C]//IEEECongress on Evolutionary Computation(CEC),Beijing,2014:3214-3221.
[12]Li Xi-guang,Han Shou-fei,Liu Xiao-jing,et a1.Fireworks algorithm based on reverse learning and dynamic memory feedback[J].Computer Engineering,2017,43(12):203-210.
[13]Li J,Zheng S,Tan Y.The effect of information utilization:introducing a novel guiding spark in the fireworks algorithm[J].IEEETransactions on Evolutionary Computation,2017,21(1):153-166.
[14]Fang Liu-ping,Wang Ji-wen,Qiu Jian-feng,et al.Dynamic search fireworks algorithm with learning factor[J].Journal of Frontiers of Computer Science and Technology,2017,11(3):491-501.
[15]Gao H,Diao M.Cultural firework algorithm and its application For digital filters design[J].International Journal of Modelling Identification&Control,2011,14(4):324-331.
[16]Yu C,Kelley L,Zheng S,et al.Fireworks algorithm with differential mutation for solving the CEC 2014 competition problems[C]//Evolutionary Computation,IEEE,2014:3238-3245.
[17]Zhang B,Zhang M X,Zheng Y J.A hybrid biogeography-based optimization and fireworks algorithm[C]//Evolutionary Computation,IEEE,2014:3200-3206.
[18]Yang X S.A new metaheuristic bat-inspired algorithm[J].Computer Knowledge&Technology,2010,284:65-74.
[19]Kennedy J,Eberhart R.Particle swarm optimization[C]//IEEEInternational Conference on Neural Networks,2002:1942-1948.
[20]Shi Y,Eberhart R.A modified particle swarm optimizer[C]//IEEE International Conference on Evolutionary Computation Proceedings,Xplore,1999:69-73.
[21]Zou D,Gao L,Li S,et al.Solving 0-1 knapsack problem by a novel global harmony search algorithm[J].Applied Soft Computing,2011,11(2):1556-1564.
[2]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.
[3]范虹,侯存存,朱艳春,等.烟花算法优化的软子空间MR图像聚类算法[J].软件学报,2017,28(11):3080-3093.
[4]杨志升,朱参世,高杨军.利用增强烟花算法对RFID网络进行规划[J].计算机工程与应用,2017,53(3):23-27.
[7]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.
[12]李席广,韩守飞,刘晓静,等.基于反向学习与动态记忆反馈的烟花算法[J].计算机工程,2017,43(12):203-210.
[14]方柳平,汪继文,邱剑锋,等.具有学习因子的动态搜索烟花算法[J].计算机科学与探索,2017,11(3):491-501.