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A modified firefly algorithm based on light intensity difference

Author

Listed:
  • Bin Wang

    (National University of Defense Technology)

  • Dong-Xu Li

    (National University of Defense Technology)

  • Jian-Ping Jiang

    (National University of Defense Technology)

  • Yi-Huan Liao

    (National University of Defense Technology)

Abstract

Firefly algorithm (FA) is a swarm-intelligence-based, meta-heuristic algorithm and has been widely applied since its establishment in 2009. In this paper, a modified FA based on light intensity difference (LFA) is proposed. The light intensity of a firefly is determined by the landscape of the objective function in FA. The modifications are established in consideration of the variation trend of light intensity differences. As the light intensity differences vary with movements of fireflies, the parameter settings could be adjusted pertinently and self-adaptively at any moment for different problems. The applications to numeric experiments show that, LFA is well adaptive and efficient for different problems, and can make a trade-off between global exploration and local exploitation so as to decrease the risk of premature convergence effectively.

Suggested Citation

  • Bin Wang & Dong-Xu Li & Jian-Ping Jiang & Yi-Huan Liao, 2016. "A modified firefly algorithm based on light intensity difference," Journal of Combinatorial Optimization, Springer, vol. 31(3), pages 1045-1060, April.
    • Handle: RePEc:spr:jcomop:v:31:y:2016:i:3:d:10.1007_s10878-014-9809-y
    DOI: 10.1007/s10878-014-9809-y
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    References listed on IDEAS

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    1. Mohammadi, Sirus & Mozafari, Babak & Solimani, Soodabeh & Niknam, Taher, 2013. "An Adaptive Modified Firefly Optimisation Algorithm based on Hong's Point Estimate Method to optimal operation management in a microgrid with consideration of uncertainties," Energy, Elsevier, vol. 51(C), pages 339-348.
    2. Younes, Mimoun & Khodja, Fouad & Kherfane, Riad Lakhdar, 2014. "Multi-objective economic emission dispatch solution using hybrid FFA (firefly algorithm) and considering wind power penetration," Energy, Elsevier, vol. 67(C), pages 595-606.
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