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The Improvement on Controlling Exploration and Exploitation of Firework Algorithm

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Advances in Swarm Intelligence (ICSI 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7928))

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Abstract

Firework algorithm (FWA) is a new Swarm Intelligence (SI) based optimization technique, which presents a different search manner and simulates the explosion of fireworks to search the optimal solution of problem. Since it was proposed, fireworks algorithm has shown its significance and superiority in dealing with the optimization problems. However, the calculation of number of explosion spark and amplitude of firework explosion of FWA should dynamically control the exploration and exploitation of searching space with iteration. The mutation operator of FWA needs to generate the search diversity. This paper provides a kind of new method to calculate the number of explosion spark and amplitude of firework explosion. By designing a transfer function, the rank number of firework is mapped to scale of the calculation of scope and spark number of firework explosion. A parameter is used to dynamically control the exploration and exploitation of FWA with iteration going on. In addition, this paper uses a new random mutation operator to control the diversity of FWA search. The modified FWA have improved the performance of original FWA. By experiment conducted by the standard benchmark functions, the performance of improved FWA can match with that of particle swarm optimization (PSO).

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Author information

Authors and Affiliations

  1. School of Information Science and Engineering, Fujian University of Technology, Fuzhou, 350108, P.R. China

    Jianhua Liu

  2. Department of Machine Intelligence, School of EECS, Peking University, China

    Jianhua Liu, Shaoqiu Zheng & Ying Tan

  3. Key Laboratory of Machine Perception (MOE), Peking University, China

    Jianhua Liu, Shaoqiu Zheng & Ying Tan

Authors
  1. Jianhua Liu
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  2. Shaoqiu Zheng
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  3. Ying Tan
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Editor information

Editors and Affiliations

  1. Key Laboratory of Machine Perception (MOE), School of lectronics Engineering and Computer Science, Department of Machine Intelligence, Peking University, 100871, Beijing, China

    Ying Tan

  2. Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, 215123, Suzhou, China

    Yuhui Shi

  3. Automation College, Harbin Engineering University, 150001, Harbin, China

    Hongwei Mo

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Liu, J., Zheng, S., Tan, Y. (2013). The Improvement on Controlling Exploration and Exploitation of Firework Algorithm. In: Tan, Y., Shi, Y., Mo, H. (eds) Advances in Swarm Intelligence. ICSI 2013. Lecture Notes in Computer Science, vol 7928. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38703-6_2

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  • DOI: https://doi.org/10.1007/978-3-642-38703-6_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38702-9

  • Online ISBN: 978-3-642-38703-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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