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Fractional-order artificial bee colony algorithm with application in robot path planning

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  • Cui, Yibing
  • Hu, Wei
  • Rahmani, Ahmed

Abstract

Artificial bee colony (ABC) algorithm is a popular meta-heuristic optimization algorithm inspired by the foraging behaviors of honeybees. Although ABC has outstanding exploration ability, it has certain weakness like poor exploitation capability and low solution precision. Therefore, to tackle these weakness and improve the performance, an ABC algorithm based on fractional-order calculus (FOABC) is proposed. More specially, the memory properties of fractional-order calculus is incorporated into onlooker bee phase to improve the local-search capability. Each time generating a new candidate solution, the previous foraging behaviors stored in memory are referred. Another enhanced search strategy is adopted in employed bee phase to avoid losing the balance between diversification and intensification. To evaluate the performance of FOABC, several groups of experiments are conducted on CEC 2017 benchmark problems. According to the experimental studies, FOABC is outstanding in comparisons with ABC variants and also performs remarkably well in practical applications, namely robot path planning.

Suggested Citation

  • Cui, Yibing & Hu, Wei & Rahmani, Ahmed, 2023. "Fractional-order artificial bee colony algorithm with application in robot path planning," European Journal of Operational Research, Elsevier, vol. 306(1), pages 47-64.
    • Handle: RePEc:eee:ejores:v:306:y:2023:i:1:p:47-64
    DOI: 10.1016/j.ejor.2022.11.007
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    References listed on IDEAS

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    1. Harish Sharma & Jagdish Chand Bansal & K. V. Arya & Xin-She Yang, 2016. "Lévy flight artificial bee colony algorithm," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(11), pages 2652-2670, August.
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    5. Ghoshal, Sudishna & Sundar, Shyam, 2020. "Two heuristics for the rainbow spanning forest problem," European Journal of Operational Research, Elsevier, vol. 285(3), pages 853-864.
    6. Fragapane, Giuseppe & de Koster, René & Sgarbossa, Fabio & Strandhagen, Jan Ola, 2021. "Planning and control of autonomous mobile robots for intralogistics: Literature review and research agenda," European Journal of Operational Research, Elsevier, vol. 294(2), pages 405-426.
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    Cited by:

    1. Muhammad Sher Ramzan & Anees Asghar & Ata Ullah & Fawaz Alsolami & Iftikhar Ahmad, 2024. "A Bee Colony-Based Optimized Searching Mechanism in the Internet of Things," Future Internet, MDPI, vol. 16(1), pages 1-16, January.

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