A multi-stage IP-based heuristic for class timetabling and trainer rostering

Czibula, O; Gu, H; Russell, A; Zinder, Y

A multi-stage IP-based heuristic for class timetabling and trainer rostering

Czibula, O

Gu, H

Russell, A Zinder, Y

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Publication Type:: Journal Article
Citation:: Annals of Operations Research, 2017, 252 (2), pp. 305 - 333
Issue Date:: 2017-05-01

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Field	Value	Language
dc.contributor.author	Czibula, O 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	Russell, A	en_US
dc.contributor.author	Zinder, Y https://orcid.org/0000-0003-2024-8129	en_US
dc.date.issued	2017-05-01	en_US
dc.identifier.citation	Annals of Operations Research, 2017, 252 (2), pp. 305 - 333	en_US
dc.identifier.issn	0254-5330	en_US
dc.identifier.uri	http://hdl.handle.net/10453/42037
dc.description.abstract	© 2015, Springer Science+Business Media New York. We consider a timetabling and rostering problem involving periodic retraining of large numbers of employees at an Australian electricity distributor. This problem is different from traditional high school and university timetabling problems studied in the literature in several aspects. We propose a three-stage heuristic consisting of timetable generation, timetable improvement, and trainer rostering. Large-scale integer linear programming models for both the timetabling and the rostering components are proposed, and several unique operational constraints are discussed. We show that this solution approach is able to produce good solutions in practically acceptable time.	en_US
dc.relation.ispartof	Annals of Operations Research	en_US
dc.relation.isbasedon	10.1007/s10479-015-2090-3	en_US
dc.subject.classification	Operations Research	en_US
dc.title	A multi-stage IP-based heuristic for class timetabling and trainer rostering	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	252	en_US
utslib.for	010303 Optimisation	en_US
utslib.for	01 Mathematical Sciences	en_US
utslib.for	08 Information and Computing Sciences	en_US
utslib.for	15 Commerce, Management, Tourism and Services	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	open_access
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	252	en_US

Abstract:

© 2015, Springer Science+Business Media New York. We consider a timetabling and rostering problem involving periodic retraining of large numbers of employees at an Australian electricity distributor. This problem is different from traditional high school and university timetabling problems studied in the literature in several aspects. We propose a three-stage heuristic consisting of timetable generation, timetable improvement, and trainer rostering. Large-scale integer linear programming models for both the timetabling and the rostering components are proposed, and several unique operational constraints are discussed. We show that this solution approach is able to produce good solutions in practically acceptable time.

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http://hdl.handle.net/10453/42037