Detecting Firefly Algorithm for Numerical Optimization

详细信息    查看全文

• 关键词：Firefly algorithm ; Detecting firefly ; Global optima
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：9712
• 期：1
• 页码：200-210
• 全文大小：2,239 KB
• 参考文献：1.Yang, X.S.: Firefly algorithm. Nature-Inspired Metaheuristic Algorithms Second Edition. Luniver Press, Bristol (2010)CrossRef
  2.Cheung, N.J., Ding, X.M., Shen, H.B.: Adaptive firefly algorithm: parameter analysis and its application. PLoS ONE 9(11), e112634 (2014)CrossRef
  3.Yang, X.S.: Firefly algorithm, stochastic test functions and design optimization. Int. J. Bio-Inspired Comput. 2(2), 78–84 (2010)CrossRef
  4.Johari, N.F., Zain, A.M., Mustaffa, N.H.: Firefly algorithm for optimization problem. Appl. Mech. Mater. 421, 512–517 (2013)CrossRef
  5.Yang, X.S.: Firefly algorithms for multimodal optimization. Stochast. Algorithms Found. Appl. 5792, 169–178 (2010)MathSciNet CrossRef MATH
  6.Maheshwar Kaushik, K., Arora, V.: A hybrid data clustering using firefly algorithm based improved genetic algorithm. Procedia Comput. Sci. 58, 249–256 (2015)CrossRef
  7.Farook, S.: Regulating LFC regulations in a deregulated power system using hybrid genetic-firefly algorithm. In: IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT), IEEE International Conference, Coimbatore, India, pp. 1–7 (2015)
  8.Arora, S., Singh, S., Singh, S., Sharma, B.: Mutated firefly algorithm. In: International Conference on Parallel, Distributed and Grid Computing, pp. 33–38 (2014)
  9.Yu, S., Zhu, S., Ma, Y., Mao, D.: A variable step size firefly algorithm for numerical optimization. Appl. Math. Comput. 263, 214–220 (2015)MathSciNet
  10.Tilahun, S.L., Ong, H.C.: Modified firefly algorithm. J. Appl. Math. 467631(12), 2428–2439 (2012)MathSciNet MATH
  11.Tian, Y., Gao, W., Yan, S.: An improved inertia weight firefly optimization algorithm and application. Int. Conf. Control Eng. Commun. Technol. Liaoning China 4, 64–68 (2012)
  12.Bidar, M., Kanan, H.R.: Jumper firefly algorithm. In: 3rd International Conference on Computer and Knowledge Engineering (ICCKE), Mashhad, Iran, pp. 267–271 (2013)
  13.Fateen, S.E.K.: Intelligent firefly algorithm for global optimization. In: Yang, X.-S. (ed.) Cuckoo Search and Firefly Algorithm. SCI, vol. 516, pp. 315–330. Springer, Heidelberg (2014)CrossRef
  14.Tuba, M., Bacanin, N.: Upgraded firefly algorithm for portfolio optimization problem. In: UK Sim-AMSS 16th International Conference on Computer Modelling and Simulation, Cambridge, USA, pp. 113–118 (2014)
  15.Yang, X.S.: Firefly algorithm, L’evy flights and global optimization. In: Bramer, M., Ellis, R., Petridis, M. (eds.) Research and Development in Intelligent Systems XXVI, Springer London, pp. 209–218 (2010)
  16.Gandomi, A.H., Yang, X.S., Talatahari, S., Alaiv, A.-H.: Firefly algorithm with chaos. Commun. Nonlinear Sci. Numer. Simul. 18(1), 89–98 (2013)MathSciNet CrossRef MATH
  17.Baykasoglu, A., Ozsoydan, F.B.: Adaptive firefly algorithm with chaos for mechanical design optimization problems. J Appl. Soft Comput. 36(c), 152–164 (2015)CrossRef
  18.Liu, C.N., Tian, Y.F., Zhang Q., Yuan J., Xue, B.B.: Adaptive firefly optimization algorithm based on stochastic inertia weight. In: Sixth International Symposium on Computational Intelligence and Design, Hangzhou, China, pp. 334–337 (2013)
  19.Zhang, Y.N., Teng, H.F.: Detecting particle swarm optimization. Concurrency Comput. Pract. Experience 21(4), 449–473 (2009)CrossRef
  20.Liang, J.J., Qu, B.Y., Suganthan, P.N., Hernández-Díaz, A.G.: Problem Definitions and Evaluation Criteria for the CEC 2013 Special Session on Real-Parameter Optimization
  
• 作者单位：Yuchen Zhang (16)
  Xiujuan Lei (16)
  Ying Tan (17)
  
  16. School of Computer Science, Shaanxi Normal University, Xi’an, 710119, China
  17. School of Electronics Engineering and Computer Science, Peking University, Beijing, 100871, China
  
• 丛书名：Advances in Swarm Intelligence
• ISBN：978-3-319-41000-5
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349
• 卷排序：9712

文摘

Firefly Algorithm (FA) is a stochastic optimization algorithm inspired by the swarm intelligence. It has the advantages of simple implementation, high efficiency and so on. However, the algorithm is easy to come into premature convergence and fall into local optimum. To address this problem, we proposed a novel firefly algorithm, Detecting Firefly Algorithm (DFA), in which we use a detecting firefly that flies round certain target points to improve the search path of standards FA. Moreover, the influence of the brightest firefly and the second brightest firefly is taken into consideration to optimize the movement strategy of the single firefly. The example illustrates that the higher precision and better convergence features of the proposed algorithm in numerical optimization.