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, Xiuli
Cheng, T. C. Edwin
Subjects: Scheduling
Single-machine
Deteriorating jobs
Learning effects
Makespan
Issue Date: Apr-2007
Publisher: Elsevier
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.
Rights: European Journal of Operational Research © 2006 Elsevier B.V. The journal web site is located at http://www.sciencedirect.com.
Type: Journal/Magazine Article
URI: http://hdl.handle.net/10397/1084
DOI: 10.1016/j.ejor.2006.01.017
ISSN: 0377-2217
Appears in Collections:LMS Journal/Magazine Articles

Files in This Item:
File Description SizeFormat 
EJORSingle-machine Scheduling with Deteriorating Jobs and Learning.pdfPre-published version317.6 kBAdobe PDFView/Open


All items in the PolyU Institutional Repository are protected by copyright, with all rights reserved, unless otherwise indicated. No item in the PolyU IR may be reproduced for commercial or resale purposes.