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A novel enhanced exploration firefly algorithm for global continuous optimization problems

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Abstract

In the global optimization process of the firefly algorithm (FA), there is a need to provide a fast convergence rate and to explore the search space more effectively. Therefore, we conduct modular analysis of the FA and propose a novel enhanced exploration firefly algorithm (EE-FA), which includes an enhanced attractiveness term module and an enhanced random term module. The attractiveness term module can improve the exploration efficiency and accelerate the convergence rate by enhancing the attraction between fireflies. The random term module improves the exploration efficiency by introducing a damped vibration distribution factor. The EE-FA uses multiple parameters to balance its exploration efficiency and convergence rate. The parameters have a great influence on the performance of the EE-FA. In order to achieve the best performance of the EE-FA, each parameter of the EE-FA needs to be simulated to determine its optimal value. Compared to multiple variants of the FA, the EE-FA has better exploration efficiency and a faster convergence speed. Experimental results reveal that the EE-FA recreated consistently vanquishes the front for 24 benchmark functions and 4 real design case studies in terms of both convergence rate and exploration efficiency.

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Acknowledgements

This work utilizes the resources and services provided by Southeast University. The platform for calculating data is supported by the laboratory of Nanjing Institute of Technology. This work was supported by National Natural Science Foundation of China (Grant No. 51705238)

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Authors and Affiliations

  1. School of Mechanical Engineering, Southeast University, No. 2, Southeast University Road, Jiangning District, Nanjing, 211189, Jiangsu, China

    Jianxun Liu, Jinfei Shi & Min Dai

  2. School of Mechanical Engineering, Nanjing Institute of Technology, Nanjing, 211167, China

    Jinfei Shi & Fei Hao

  3. College of Mechanical and Electrical Engineering, Guangdong Polytechnic of Industry and Commerce, Guangzhou, 510510, China

    Xiaoya Zhang

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  1. Jianxun Liu
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  2. Jinfei Shi
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  3. Fei Hao
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  4. Min Dai
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  5. Xiaoya Zhang
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Contributions

JL conceptualization, investigation, methodology, validation, software, writing, revision, review and editing, visualization; JS supervision, project administration, funding acquisition; FH methodology, formal analysis; writing, revision; formal analysis; MD software, revision, review, conceptualization, formal analysis; XZ revision, review, analysis.

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Correspondence to Jianxun Liu or Jinfei Shi.

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Liu, J., Shi, J., Hao, F. et al. A novel enhanced exploration firefly algorithm for global continuous optimization problems. Engineering with Computers 38 (Suppl 5), 4479–4500 (2022). https://doi.org/10.1007/s00366-021-01477-6

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  • DOI: https://doi.org/10.1007/s00366-021-01477-6

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