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Cooperative Bacterial Foraging Optimization

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  • Hanning Chen
  • Yunlong Zhu
  • Kunyuan Hu

Abstract

Bacterial Foraging Optimization (BFO) is a novel optimization algorithm based on the social foraging behavior of E. coli bacteria. This paper presents a variation on the original BFO algorithm, namely, the Cooperative Bacterial Foraging Optimization (CBFO), which significantly improve the original BFO in solving complex optimization problems. This significant improvement is achieved by applying two cooperative approaches to the original BFO, namely, the serial heterogeneous cooperation on the implicit space decomposition level and the serial heterogeneous cooperation on the hybrid space decomposition level. The experiments compare the performance of two CBFO variants with the original BFO, the standard PSO and a real-coded GA on four widely used benchmark functions. The new method shows a marked improvement in performance over the original BFO and appears to be comparable with the PSO and GA.

Suggested Citation

  • Hanning Chen & Yunlong Zhu & Kunyuan Hu, 2009. "Cooperative Bacterial Foraging Optimization," Discrete Dynamics in Nature and Society, Hindawi, vol. 2009, pages 1-17, November.
  • Handle: RePEc:hin:jnddns:815247
    DOI: 10.1155/2009/815247
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    Cited by:

    1. Cazzolla Gatti, Roberto, 2021. "A multi-armed bandit algorithm speeds up the evolution of cooperation," Ecological Modelling, Elsevier, vol. 439(C).

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