Scheduling personnel retraining: Column generation heuristics

Czibula, OG; Gu, H; Zinder, Y

Scheduling personnel retraining: Column generation heuristics

Czibula, OG

Gu, H

Zinder, Y

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2016, 9849 LNCS pp. 213 - 224
Issue Date:: 2016-01-01

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Field	Value	Language
dc.contributor.author	Czibula, OG https://orcid.org/0000-0002-9788-9189	en_US
dc.contributor.author	Gu, H https://orcid.org/0000-0003-2035-2583	en_US
dc.contributor.author	Zinder, Y https://orcid.org/0000-0003-2024-8129	en_US
dc.date.issued	2016-01-01	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2016, 9849 LNCS pp. 213 - 224	en_US
dc.identifier.isbn	9783319455860	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/101927
dc.description.abstract	© Springer International Publishing Switzerland 2016. Many organisations need periodic retraining of staff. Due to certain requirements on the composition of study groups, the planning of training sessions is an NP-hard problem. The paper presents linear and nonlinear mathematical programming formulations of this problem together with three column generation based heuristic optimisation procedures. The procedures are compared by means of computational experiments that use data originating from a large Australian electricity distributor with several thousand employees.	en_US
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en_US
dc.relation.isbasedon	10.1007/978-3-319-45587-7_19	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Scheduling personnel retraining: Column generation heuristics	en_US
dc.type	Conference Proceeding
utslib.citation.volume	9849 LNCS	en_US
utslib.for	010303 Optimisation	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
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	9849 LNCS	en_US

Abstract:

© Springer International Publishing Switzerland 2016. Many organisations need periodic retraining of staff. Due to certain requirements on the composition of study groups, the planning of training sessions is an NP-hard problem. The paper presents linear and nonlinear mathematical programming formulations of this problem together with three column generation based heuristic optimisation procedures. The procedures are compared by means of computational experiments that use data originating from a large Australian electricity distributor with several thousand employees.

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http://hdl.handle.net/10453/101927