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

2.50
Hdl Handle:
http://hdl.handle.net/10547/593537
Title:
Adaptive bees algorithm : bioinspiration from honeybee foraging to optimize fuel economy of a semi-track air-cushion vehicle
Authors:
Xu, Shuo; Yu, Fan; Luo, Zhe; Ji, Ze; Pham, Duc Truong; Qiu, Renxi
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.
Affiliation:
Shanghai Jiao Tong University; Cardiff University
Citation:
Xu, S. et al (2011) 'Adaptive Bees Algorithm--Bioinspiration from Honeybee Foraging to Optimize Fuel Economy of a Semi-Track Air-Cushion Vehicle' The Computer Journal 54 (9):1416
Publisher:
Oxford University Press
Journal:
The Computer Journal
Issue Date:
4-Jan-2011
URI:
http://hdl.handle.net/10547/593537
DOI:
10.1093/comjnl/bxq097
Additional Links:
http://comjnl.oxfordjournals.org/cgi/doi/10.1093/comjnl/bxq097
Type:
Article
Language:
en
ISSN:
0010-4620; 1460-2067
Appears in Collections:
Centre for Research in Distributed Technologies (CREDIT)

Full metadata record

DC FieldValue Language
dc.contributor.authorXu, Shuoen
dc.contributor.authorYu, Fanen
dc.contributor.authorLuo, Zheen
dc.contributor.authorJi, Zeen
dc.contributor.authorPham, Duc Truongen
dc.contributor.authorQiu, Renxien
dc.date.accessioned2016-01-15T13:23:48Zen
dc.date.available2016-01-15T13:23:48Zen
dc.date.issued2011-01-04en
dc.identifier.citationXu, S. et al (2011) 'Adaptive Bees Algorithm--Bioinspiration from Honeybee Foraging to Optimize Fuel Economy of a Semi-Track Air-Cushion Vehicle' The Computer Journal 54 (9):1416en
dc.identifier.issn0010-4620en
dc.identifier.issn1460-2067en
dc.identifier.doi10.1093/comjnl/bxq097en
dc.identifier.urihttp://hdl.handle.net/10547/593537en
dc.description.abstractThis 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.en
dc.language.isoenen
dc.publisherOxford University Pressen
dc.relation.urlhttp://comjnl.oxfordjournals.org/cgi/doi/10.1093/comjnl/bxq097en
dc.rightsArchived with thanks to The Computer Journalen
dc.subjectadaptive bees algorithmen
dc.subjectbioinspirationen
dc.subjectadaptive patch size adjustmenten
dc.subjectsemi-track air-cushion vehicleen
dc.subjectfuel economy optimizationen
dc.titleAdaptive bees algorithm : bioinspiration from honeybee foraging to optimize fuel economy of a semi-track air-cushion vehicleen
dc.typeArticleen
dc.contributor.departmentShanghai Jiao Tong Universityen
dc.contributor.departmentCardiff Universityen
dc.identifier.journalThe Computer Journalen
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