Timetabling of Workplace Training: A Combination of Mathematical Programming and Simulated Annealing

Czibula, O; Gu, H; Zinder, Y

Timetabling of Workplace Training: A Combination of Mathematical Programming and Simulated Annealing

Czibula, O

Gu, H

Zinder, Y

Permalink

Publisher:: PATAT
Publication Type:: Conference Proceeding
Citation:: PATAT 2016: Proceedings of the 11th International Conference of the Practice and Theory of Automated Timetabling, 2016, pp. 95 - 107 (13)
Issue Date:: 2016-01-01

Closed Access

	Filename	Description	Size
	paper_10.pdf	Published version	1.04 MB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

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	Zinder, Y	en_US
dc.contributor.editor	Burke, EK	en_US
dc.contributor.editor	Gaspero, LD	en_US
dc.contributor.editor	Ozcan, E	en_US
dc.contributor.editor	McCollum, B	en_US
dc.contributor.editor	Schaerf, A	en_US
dc.date	2016-08-23	en_US
dc.date.issued	2016-01-01	en_US
dc.identifier.citation	PATAT 2016: Proceedings of the 11th International Conference of the Practice and Theory of Automated Timetabling, 2016, pp. 95 - 107 (13)	en_US
dc.identifier.isbn	978-0-9929984-1-7	en_US
dc.identifier.uri	http://hdl.handle.net/10453/57530
dc.description.abstract	The paper is concerned with the problem of scheduling workplace training, which arises in a broad range of organisations, from the hospital placements of nursing students to apprentice training at organisations such as electricity distributors. The problem can be viewed as a generalisation of the open shop scheduling problem. The paper discusses the complexity of the considered problem, and presents an optimisation procedure, which is a sequential application of integer linear programming and simulated annealing. The effectiveness of the proposed optimisation procedure was demonstrated by computational experiments using data with typical characteristics of a real world problems arising at large electricity distributors. The computational experiments show that the proposed optimisation procedure produces superior solutions on average compared to those from a general purpose MIP solver.	en_US
dc.publisher	PATAT	en_US
dc.relation.ispartof	PATAT 2016: Proceedings of the 11th International Conference of the Practice and Theory of Automated Timetabling	en_US
dc.relation.ispartof	International Conference of the Practice and Theory of Automated Timetabling	en_US
dc.title	Timetabling of Workplace Training: A Combination of Mathematical Programming and Simulated Annealing	en_US
dc.type	Conference Proceeding
utslib.location.activity	Udine, Italy	en_US
utslib.for	0102 Applied Mathematics	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.consider-herdc	true	en_US
pubs.finish-date	2016-08-26	en_US
pubs.publication-status	Published online	en_US
pubs.start-date	2016-08-23	en_US

Abstract:

The paper is concerned with the problem of scheduling workplace training, which arises in a broad range of organisations, from the hospital placements of nursing students to apprentice training at organisations such as electricity distributors. The problem can be viewed as a generalisation of the open shop scheduling problem. The paper discusses the complexity of the considered problem, and presents an optimisation procedure, which is a sequential application of integer linear programming and simulated annealing. The effectiveness of the proposed optimisation procedure was demonstrated by computational experiments using data with typical characteristics of a real world problems arising at large electricity distributors. The computational experiments show that the proposed optimisation procedure produces superior solutions on average compared to those from a general purpose MIP solver.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/57530