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Cuckoo Search and Firefly Algorithm pp 315–330Cite as

Intelligent Firefly Algorithm for Global Optimization

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 516))

Abstract

Intelligent firefly algorithm (IFA) is a novel global optimization algorithm that aims to improve the performance of the firefly algorithm (FA), which was inspired by the flashing communication signals among firefly swarms. This chapter introduces the IFA modification and evaluates its performance in comparison with the original algorithm in twenty multi-dimensional benchmark problems. The results of those numerical experiments show that IFA outperformed FA in terms of reliability and effectiveness in all tested benchmark problems. In some cases, the global minimum could not have been successfully identified via the firefly algorithm, except with the proposed modification for FA.

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References

  1. Floudas, C.A., Gounaris, C.E.: A review of recent advances in global optimization. J. Glob. Optim. 45, 3–38 (2008)

    Article  MathSciNet  Google Scholar 

  2. Rajabioun, R.: Cuckoo optimization algorithm. Appl. Soft Comput. 11, 5508–5518 (2011)

    Article  Google Scholar 

  3. Karaboga, D., Basturk, B.: On the performance of artificial bee colony (ABC) algorithm. Appl. Soft Comp. 8, 687–697 (2008)

    Article  Google Scholar 

  4. Li, G., Niu, P., Xiao, X.: Development and investigation of efficient artificial bee colony algorithm for numerical function optimization. Appl. Soft Comp. 12, 320–332 (2012)

    Article  Google Scholar 

  5. Omkar, S.N., Senthilnath, J., Khandelwal, R., Narayana Naik, G., Gopalakrishnan, S.: Artificial bee colony (ABC) for multi-objective design optimization of composite structures. Appl. Soft Comp. 11, 489–499 (2011)

    Article  Google Scholar 

  6. Marinaki, M., Marinakis, Y., Zopounidis, C.: Honey bees mating optimization algorithm for financial classification problems. Appl. Soft Comp. 10, 806–812 (2010)

    Article  Google Scholar 

  7. Chen, H., Zhu, Y., Hu, K.: Multi-colony bacteria foraging optimization with cell-to-cell communication for RFID network planning. Appl. Soft Comp. 10, 539–547 (2010)

    Article  Google Scholar 

  8. Yang, X.S.: Firefly algorithm. Nature-Inspired Metaheuristic AlgorithmsLuniver Press, UK (2008)

    Google Scholar 

  9. Sayadi, M.K., Ramezanian, R., Ghaffari-Nasab, N.: A discrete firefly meta-heuristic with local search for makespan minimization in permutation flow shop scheduling problems. Int. J. Ind. Eng. Comput. 1, 1–10 (2010)

    Article  Google Scholar 

  10. Apostolopoulos, T., Vlachos, A.: Application of the firefly algorithm for solving the economic emissions load dispatch problem. Int. J. Comb. ID 523806, 1–23 (2011)

    MathSciNet  Google Scholar 

  11. B. Rampriya, K. Mahadevan, and S. Kannan, Unit commitment in deregulated power system using Lagrangian firefly algorithm, In: International Conference on Communication Control and Computing Technologies, pp. 389–393, 2010.

    Google Scholar 

  12. dos Santos Coelho, L., de Andrade Bernert, D.L., Mariani, V.C.: A chaotic firefly algorithm applied to reliability-redundancy optimization. In: IEEE Congr. Evol. Comput. 2011, 517–521 (2011)

    Google Scholar 

  13. Giannakouris, G., Vassiliadis, V., and Dounias, G. Experimental Study on a Hybrid Nature-Inspired Algorithm for Financial Portfolio Optimizatio. In: Konstantopoulos, S., Perantonis, S., Karkaletsis, V., Spyropoulos, C. and Vouros, G. (eds.) Artificial Intelligence: Theories, Models and Applications, vol. 6040, pp. 101–111. Springer, Berlin / Heidelberg, (2010)

    Google Scholar 

  14. Gandomi, A.H., Yang, X.S., Alavi, A.H.: Mixed variable structural optimization using firefly algorithm. Comp. Struct. 89, 2325–2336 (2011)

    Article  Google Scholar 

  15. Yang, X.S., Sadat Hosseini, S.S., Gandomi, A.H.: Firefly algorithm for solving non-convex economic dispatch problems with valve loading effect. Appl. Soft Comp. 12, 1180–1186 (2012)

    Article  Google Scholar 

  16. Yang, X.S.: Review of meta-heuristics and generalised evolutionary walk algorithm. Int. J. Bio-Insp. Comput. 3, 77–84 (2011)

    Article  Google Scholar 

  17. Dolan, E.D., Moré, J.J.: Benchmarking optimization software with performance profiles. Math. Program. 91, 201–213 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  18. Ali, M.M., Khompatraporn, C., Zabinsky, Z.B.: A numerical evaluation of several stochastic algorithms on selected continuous global optimization test problems. J. Glob. Optim. 31, 635–672 (2005)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Chemical Engineering, Cairo University, Giza, Egypt

    Seif-Eddeen K. Fateen

  2. Department of Chemical Engineering, Instituto Tecnológico de Aguascalientes, Aguascalientes, México

    Adrián Bonilla-Petriciolet

Authors
  1. Seif-Eddeen K. Fateen
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  2. Adrián Bonilla-Petriciolet
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Corresponding author

Correspondence to Adrián Bonilla-Petriciolet .

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Editors and Affiliations

  1. School of Science and Technology, Middlesex University, London, United Kingdom

    Xin-She Yang

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© 2014 Springer International Publishing Switzerland

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Fateen, SE.K., Bonilla-Petriciolet, A. (2014). Intelligent Firefly Algorithm for Global Optimization. In: Yang, XS. (eds) Cuckoo Search and Firefly Algorithm. Studies in Computational Intelligence, vol 516. Springer, Cham. https://doi.org/10.1007/978-3-319-02141-6_15

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  • DOI: https://doi.org/10.1007/978-3-319-02141-6_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-02140-9

  • Online ISBN: 978-3-319-02141-6

  • eBook Packages: EngineeringEngineering (R0)

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