A genetic algorithm for assigning train arrival dates at a maintenance centre

Gu, H; Joyce, M; Lam, HC; Woods, M; Zinder, Y

A genetic algorithm for assigning train arrival dates at a maintenance centre

Gu, H

Joyce, M Lam, HC Woods, M Zinder, Y

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Publication Type:: Conference Proceeding
Citation:: IFAC-PapersOnLine, 2019, 52 (13), pp. 957 - 962
Issue Date:: 2019-09-01

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Field	Value	Language
dc.contributor.author	Gu, H https://orcid.org/0000-0003-2035-2583	en_US
dc.contributor.author	Joyce, M	en_US
dc.contributor.author	Lam, HC	en_US
dc.contributor.author	Woods, M	en_US
dc.contributor.author	Zinder, Y https://orcid.org/0000-0003-2024-8129	en_US
dc.date.issued	2019-09-01	en_US
dc.identifier.citation	IFAC-PapersOnLine, 2019, 52 (13), pp. 957 - 962	en_US
dc.identifier.uri	http://hdl.handle.net/10453/137890
dc.description.abstract	© 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. The paper is concerned with planning heavy maintenance of train-sets at a maintenance centre. The heavy maintenance process is complex and, for each train-set, the actual duration of maintenance is uncertain at the time of planning. The allocation of the dates when train-sets should arrive at the maintenance centre is crucial phase of the planning procedure. The objective function is a weighted sum of two components, the expected total penalty for not meeting the required number of train-sets in active service and the total cost for the deviation (earliness and tardiness) from the desired dates of arrival. A genetic algorithm is presented for the considered problem and its effectiveness is demonstrated by the computational experiments that used real-world data provided by a big maintenance centre.	en_US
dc.relation.ispartof	IFAC-PapersOnLine	en_US
dc.relation.isbasedon	10.1016/j.ifacol.2019.11.318	en_US
dc.title	A genetic algorithm for assigning train arrival dates at a maintenance centre	en_US
dc.type	Conference Proceeding
utslib.citation.volume	13	en_US
utslib.citation.volume	52	en_US
utslib.for	0102 Applied Mathematics	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 Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
utslib.copyright.status	open_access
pubs.issue	13	en_US
pubs.publication-status	Published	en_US
pubs.volume	52	en_US

Abstract:

© 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. The paper is concerned with planning heavy maintenance of train-sets at a maintenance centre. The heavy maintenance process is complex and, for each train-set, the actual duration of maintenance is uncertain at the time of planning. The allocation of the dates when train-sets should arrive at the maintenance centre is crucial phase of the planning procedure. The objective function is a weighted sum of two components, the expected total penalty for not meeting the required number of train-sets in active service and the total cost for the deviation (earliness and tardiness) from the desired dates of arrival. A genetic algorithm is presented for the considered problem and its effectiveness is demonstrated by the computational experiments that used real-world data provided by a big maintenance centre.

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http://hdl.handle.net/10453/137890