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Adaptive bees algorithm—bioinspiration from honeybee foraging to optimize fuel economy of a semi-track air-cushion vehicle

  • ,
  • Shuo Xu
    ,
  • Fan Yu
    ,
  • Zhe Luo
    ,
  • Ze Ji
    ,
  • Duc Truong Pham
  • Shanghai Jiao Tong University
    ,
  • Cardiff University
Research Output: Contribution to journal Article Peer-review

Abstract

This interdisciplinary study covers bionics, optimization and vehicle engineering. Semi-track air-cushion vehicle (STACV) provides a solution to transportation on soft terrain, whereas it also brings a new problem of excessive fuel consumption. By mimicking the foraging behaviour of honeybees, the bioinspired adaptive bees algorithm (ABA) is proposed to calculate its running parameters for fuel economy optimization. Inherited from the basic algorithm prototype, it involves parallel-operated global search and local search, which undertake exploration and exploitation, respectively. The innovation of this improved algorithm lies in the adaptive adjustment mechanism of the range of local search (called ‘patch size’) according to the source and the rate of change of the current optimum. Three gradually in-depth experiments are implemented for 143 kinds of soils. First, the two optimal STACV running parameters present the same increasing or decreasing trend with soil parameters. This result is consistent with the terramechanics-based theoretical analysis. Second, the comparisons with four alternative algorithms exhibit the ABA's effectiveness and efficiency, and accordingly highlight the advantage of the novel adaptive patch size adjustment mechanism. Third, the impacts of two selected optimizer parameters to optimization accuracy and efficiency are investigated and their recommended values are thus proposed.

Publication Information

Output type

Research Output: Contribution to journal Article Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 1416-1426

Journal (Volume, Issue Number)

Computer Journal (Volume 54, Issue 9)

Publication milestones

  • Published - 04/01/2011

Publication status

Published - 04/01/2011

ISSN

0010-4620

External Publication IDs

  • handle.net: 10547/593537
  • Scopus: 80052604198

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