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Detecting Firefly Algorithm for Numerical Optimization

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Advances in Swarm Intelligence (ICSI 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9712))

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Abstract

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.

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Acknowledgments

This paper is supported by the National Natural Science Foundation of China (61502290, 61401263), Industrial Research Project of Science and Technology in Shaanxi Province(2015GY016), the Fundamental Research Funds for the Central Universities, Shaanxi Normal University (GK201501008) and China Postdoctoral Science Foundation (2015M582606).

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Authors and Affiliations

  1. School of Computer Science, Shaanxi Normal University, Xi’an, 710119, China

    Yuchen Zhang & Xiujuan Lei

  2. School of Electronics Engineering and Computer Science, Peking University, Beijing, 100871, China

    Ying Tan

Authors
  1. Yuchen Zhang
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  2. Xiujuan Lei
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  3. Ying Tan
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Corresponding author

Correspondence to Xiujuan Lei .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Xi'an Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

  3. Shenzhen University, Shenzhen, China

    Ben Niu

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© 2016 Springer International Publishing Switzerland

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Zhang, Y., Lei, X., Tan, Y. (2016). Detecting Firefly Algorithm for Numerical Optimization. In: Tan, Y., Shi, Y., Niu, B. (eds) Advances in Swarm Intelligence. ICSI 2016. Lecture Notes in Computer Science(), vol 9712. Springer, Cham. https://doi.org/10.1007/978-3-319-41000-5_20

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  • DOI: https://doi.org/10.1007/978-3-319-41000-5_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40999-3

  • Online ISBN: 978-3-319-41000-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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