Single-machine scheduling with deteriorating jobs and learning effects to minimize the makespan

Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1084

Title:	Single-machine scheduling with deteriorating jobs and learning effects to minimize the makespan
Authors:	Wang, X Cheng, TCE
Issue Date:	Apr-2007
Source:	European journal of operational research, 1 Apr. 2007, v. 178, no. 1, p. 57-70
Abstract:	This paper studies the single-machine scheduling problem with deteriorating jobs and learning considerations. The objective is to minimize the makespan. We first show that the schedule produced by the largest growth rate rule is unbounded for our model, although it is an optimal solution for the scheduling problem with deteriorating jobs and no learning. We then consider three special cases of the problem, each corresponding to a specific practical scheduling scenario. Based on the derived optimal properties, we develop an optimal algorithm for each of these cases. Finally, we consider a relaxed model of the second special case, and present a heuristic and analyze its worst-case performance bound.
Keywords:	Scheduling Single-machine Deteriorating jobs Learning effects Makespan
Publisher:	Elsevier
Journal:	European journal of operational research
ISSN:	0377-2217
EISSN:	1872-6860
DOI:	10.1016/j.ejor.2006.01.017
Rights:	European Journal of Operational Research © 2006 Elsevier B.V. The journal web site is located at http://www.sciencedirect.com.
Appears in Collections:	Journal/Magazine Article

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Status	open access
File Version	Final Accepted Manuscript

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