Deadlock Prediction And Avoidance For Zone-Control AGVS

Yeh, MS; Yeh, W

Deadlock Prediction And Avoidance For Zone-Control AGVS

Yeh, MS Yeh, W

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Publisher:: Taylor & Francis Ltd
Publication Type:: Journal Article
Citation:: International Journal Of Production Research, 1998, 36 (10), pp. 2879 - 2889
Issue Date:: 1998-01

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Field	Value	Language
dc.contributor.author	Yeh, MS	en_US
dc.contributor.author	Yeh, W	en_US
dc.date.issued	1998-01	en_US
dc.identifier.citation	International Journal Of Production Research, 1998, 36 (10), pp. 2879 - 2889	en_US
dc.identifier.issn	0020-7543	en_US
dc.identifier.uri	http://hdl.handle.net/10453/14525
dc.description.abstract	Deadlock problems of zone-control uni-directional automated guided vehicle systems (AGVS) are discussed in this paper. A directed graph is de® ned to model the vehicle ¯ ows, to identify distinct vehicle ¯ ows, to represent states easily and to capture concurrent behaviour of zone-control AGVS. The motivation of this research was to propose a dynamic approach to enable prediction in real time and to avoid deadlocks that are caused by sharing guidepath zones for a class of AGVS so that both utilization of resource and overall throughput can be improved. The proposed algorithmic procedure, in accordance with the states gained and generated from the obtained model, can serve as a functional module for the operation of a zone-control AGVS without the need to revise the original vehicle control extensively.	en_US
dc.publisher	Taylor & Francis Ltd	en_US
dc.relation.ispartof	International Journal Of Production Research	en_US
dc.relation.isbasedon	10.1080/002075498192526	en_US
dc.subject.classification	Operations Research	en_US
dc.title	Deadlock Prediction And Avoidance For Zone-Control AGVS	en_US
dc.type	Journal Article
utslib.citation.volume	10	en_US
utslib.citation.volume	36	en_US
utslib.location.activity	ISI:000076201800013	en_US
utslib.for	0102 Applied Mathematics	en_US
dc.location.activity	ISI:000076201800013	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Software
pubs.organisational-group	/University of Technology Sydney/Strength - AAI - Advanced Analytics Institute Research Centre
utslib.copyright.status	closed_access
pubs.consider-herdc	false	en_US
pubs.issue	10	en_US
pubs.volume	36	en_US

Abstract:

Deadlock problems of zone-control uni-directional automated guided vehicle systems (AGVS) are discussed in this paper. A directed graph is de® ned to model the vehicle ¯ ows, to identify distinct vehicle ¯ ows, to represent states easily and to capture concurrent behaviour of zone-control AGVS. The motivation of this research was to propose a dynamic approach to enable prediction in real time and to avoid deadlocks that are caused by sharing guidepath zones for a class of AGVS so that both utilization of resource and overall throughput can be improved. The proposed algorithmic procedure, in accordance with the states gained and generated from the obtained model, can serve as a functional module for the operation of a zone-control AGVS without the need to revise the original vehicle control extensively.

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http://hdl.handle.net/10453/14525