Uniform parallel-machine scheduling to minimize makespan with position-based learning curves

Lee, W; Chuang, M; Yeh, W

Uniform parallel-machine scheduling to minimize makespan with position-based learning curves

Lee, W Chuang, M Yeh, W

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Publisher:: Elsevier
Publication Type:: Journal Article
Citation:: Computers and Industrial Engineering, 2012, 63 (4), pp. 813 - 818
Issue Date:: 2012-01

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Field	Value	Language
dc.contributor.author	Lee, W	en_US
dc.contributor.author	Chuang, M	en_US
dc.contributor.author	Yeh, W	en_US
dc.date.issued	2012-01	en_US
dc.identifier.citation	Computers and Industrial Engineering, 2012, 63 (4), pp. 813 - 818	en_US
dc.identifier.issn	0360-8352	en_US
dc.identifier.uri	http://hdl.handle.net/10453/22840
dc.description.abstract	Scheduling with learning effects has become a popular topic in the past decade; however, most of the research focuses on single-machine problems. In many situations, there are machines in parallel and the skills of workers might be different due to their individual experience. In this paper, we study a uniform parallel machine problem in which the objective is to jointly find an optimal assignment of operators to machines and an optimal schedule to minimize the makespan. Two heuristic algorithms are proposed and computational experiments are conducted to evaluate their performance.	en_US
dc.publisher	Elsevier	en_US
dc.relation.ispartof	Computers and Industrial Engineering	en_US
dc.relation.isbasedon	10.1016/j.cie.2012.05.003	en_US
dc.subject.classification	Industrial Engineering & Automation	en_US
dc.title	Uniform parallel-machine scheduling to minimize makespan with position-based learning curves	en_US
dc.type	Journal Article
utslib.citation.volume	4	en_US
utslib.citation.volume	63	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	01 Mathematical Sciences	en_US
utslib.for	08 Information and Computing Sciences	en_US
utslib.for	09 Engineering	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	true	en_US
pubs.issue	4	en_US
pubs.volume	63	en_US

Abstract:

Scheduling with learning effects has become a popular topic in the past decade; however, most of the research focuses on single-machine problems. In many situations, there are machines in parallel and the skills of workers might be different due to their individual experience. In this paper, we study a uniform parallel machine problem in which the objective is to jointly find an optimal assignment of operators to machines and an optimal schedule to minimize the makespan. Two heuristic algorithms are proposed and computational experiments are conducted to evaluate their performance.

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http://hdl.handle.net/10453/22840