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International Symposium on Computational Intelligence and Intelligent Systems

ISICA 2015: Computational Intelligence and Intelligent Systems pp 13–22Cite as

A New Firefly Algorithm with Local Search for Numerical Optimization

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 575))

Abstract

Firefly algorithm (FA) is a recently proposed swarm intelligence optimization technique, which has shown good performance on many optimization problems. In the standard FA and its most variants, a firefly moves to other brighter fireflies. If the current firefly is brighter than another one, the current one will not be conducted any search. In this paper, we propose a new firefly algorithm (called NFA) to address this issue. In NFA, brighter fireflies can move to other positions based on local search. To verify the performance of NFA, thirteen classical benchmark functions are tested. Experimental results show that our NFA outperforms the standard FA and two other modified FAs.

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References

  1. Yang, X.S.: Engineering Optimization: An Introduction with Metaheuristic Applications. Wiley, Hoboken (2010)

    Book  Google Scholar 

  2. Chandrasekaran, K., Simon, S.P., Padhy, N.P.: Binary real coded firefly algorithm for solving unit commitment problem. Inf. Sci. 249, 67–84 (2013)

    Article  Google Scholar 

  3. Coelho, L.S., Mariani, V.C.: Improved firefly algorithm approach applied to chiller loading for energy conservation. Energy Build. 59, 273–278 (2013)

    Article  Google Scholar 

  4. Gandomi, A.H., Yang, X.S., Alavi, A.H.: Mixed variable structural optimization using firefly algorithm. Comput. Struct. 89(23–24), 2325–2336 (2013)

    Google Scholar 

  5. Miguel, L.F.F., Lopez, R.H., Miguel, L.F.F.: Multimodal size, shape, and topology optimisation of truss structures using the firefly algorithm. Adv. Eng. Softw. 56, 23–37 (2013)

    Article  Google Scholar 

  6. Marichelvam, M.K., Prabaharan, T., Yang, X.S.: A discrete firefly algorithm for the multi-objective hybrid flowshop scheduling problems. IEEE Trans. Evol. Comput. 18(2), 301–305 (2014)

    Article  Google Scholar 

  7. Farahani, S.M., Abshouri, A.A., Nasiri, B., Meybodi, M.R.: A gaussian firefly algorithm. Int. J. Mach. Learn. Comput. 1(5), 448–453 (2011)

    Article  Google Scholar 

  8. Tilahun, S.L., Ong, H.C.: Modified firefly algorithm. J. Appl. Math. Article ID 467631 (2012). doi:10.1155/2012/467631

    Google Scholar 

  9. Fister Jr., I., Yang, X.S., Fister, I., Brest, J.: Memetic firefly algorithm for combinatorial optimization. In: Filipic, B., Silc, J. (eds.) Bioinspired Optimization Methods and their Applications (BIOMA 2012). Jozef Stefan Institute, Ljubljana, Slovenia (2012)

    Google Scholar 

  10. Wang, H., Wang, W.J., Sun, H., Rahnamayan, S.: Firefly Algorithm with Random Attraction. Int. J. Bio-Inspired Comput. (2016, to be published)

    Google Scholar 

  11. Gandomi, A.H., Yang, X.S., Talatahari, S., Alavi, A.H.: Firefly algorithm with chaos. Commun. Nonlinear Sci. Numer. Simul. 18(1), 89–98 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  12. Fister, I., Yang, X.S., Brest, J., Fister Jr., I.: Modified firefly algorithm using quaternion representation. Expert Syst. Appl. 40(18), 7220–7230 (2013)

    Article  Google Scholar 

  13. Yu, S.H., Su, S.B., Lu, Q.P., Huang, L.: A novel wise step strategy for firefly algorithm. Int. J. Comput. Math. 91(12), 2507–2513 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  14. Yu, S.H., Zhu, S.L., Ma, Y., Mao, D.M.: A variable step size firefly algorithm for numerical optimization. Appl. Math. Comput. 263, 214–220 (2015)

    Article  MathSciNet  Google Scholar 

  15. Wang, H., Wu, Z.J., Rahnamayan, S., Liu, Y., Ventresca, M.: Enhancing particle swarm optimization using generalized opposition-based learning. Inf. Sci. 181(20), 4699–4714 (2011)

    Article  MathSciNet  Google Scholar 

  16. Wang, H., Rahnamayan, S., Sun, H., Omran, M.G.H.: Gaussian bare-bones differential evolution. IEEE Trans. Cybern. 43(2), 634–647 (2013)

    Article  Google Scholar 

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Acknowledgement

This work is supported by the Humanity and Social Science Foundation of Ministry of Education of China (No. 13YJCZH174), the National Natural Science Foundation of China (Nos. 61305150 and 61261039), the Science and Technology Plan Project of Jiangxi Provincial Education Department (Nos. GJJ14747 and GJJ13762), and the Natural Science Foundation of Jiangxi Province (No. 20142BAB217020).

Author information

Authors and Affiliations

  1. School of Information Engineering, Nanchang Institute of Technology, Nanchang, 330099, China

    Hui Wang, Hui Sun, Jia Zhao & Hai Zhang

  2. Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing, Nanchang, 330099, China

    Hui Wang, Hui Sun, Jia Zhao & Hai Zhang

  3. School of Business Administration, Nanchang Institute of Technology, Nanchang, 330099, China

    Wenjun Wang

  4. School of Computer, Wuhan University, Wuhan, 430072, China

    Jin Liu

  5. College of Computer and Information Engineering, Jiangxi Normal University, Nanchang, 330022, China

    Xinyu Zhou

Authors
  1. Hui Wang
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  2. Wenjun Wang
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  3. Hui Sun
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  4. Jia Zhao
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  5. Hai Zhang
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  6. Jin Liu
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  7. Xinyu Zhou
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Corresponding author

Correspondence to Hui Wang .

Editor information

Editors and Affiliations

  1. College of Mathematics and Informatics, The South China Agricultural University, Guangzhou, China

    Kangshun Li

  2. School of Computer Science, Guangzhou University, Guangzhou, China

    Jin Li

  3. School of Computer Science and Engineeri, The University of Aizu, Aizu-Wakamatsu, Fukushima, Japan

    Yong Liu

  4. Dept. of Informatics, University of Salerno, Fisciano, Italy

    Aniello Castiglione

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© 2016 Springer Science+Business Media Singapore

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Wang, H. et al. (2016). A New Firefly Algorithm with Local Search for Numerical Optimization. In: Li, K., Li, J., Liu, Y., Castiglione, A. (eds) Computational Intelligence and Intelligent Systems. ISICA 2015. Communications in Computer and Information Science, vol 575. Springer, Singapore. https://doi.org/10.1007/978-981-10-0356-1_2

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  • DOI: https://doi.org/10.1007/978-981-10-0356-1_2

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-0355-4

  • Online ISBN: 978-981-10-0356-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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