Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/9144
Title: Two-machine flowshop scheduling with truncated learning to minimize the total completion time
Authors: Li, DC
Hsu, PH
Wu, CC
Cheng, TCE 
Keywords: Scheduling
Simulated annealing
Truncated learning function
Two-machine flowshop
Issue Date: 2011
Source: Computers and industrial engineering, 2011, v. 61, no. 3, p. 655-662 How to cite?
Journal: Computers and Industrial Engineering 
Abstract: Scheduling with learning effects has received a lot of research attention lately. However, the flowshop setting is relatively unexplored. On the other hand, the actual processing time of a job under an uncontrolled learning effect will drop to zero precipitously as the number of jobs increases. This is rather absurd in reality. Motivated by these observations, we consider a two-machine flowshop scheduling problem in which the actual processing time of a job in a schedule is a function of the job's position in the schedule and a control parameter of the learning function. The objective is to minimize the total completion time. We develop a branch-and-bound and three simulated annealing algorithms to solve the problem. Computational results show that the proposed algorithms are efficient in producing near-optimal solutions.
URI: http://hdl.handle.net/10397/9144
ISSN: 0360-8352
DOI: 10.1016/j.cie.2011.04.021
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

10
Last Week
0
Last month
0
Citations as of Jun 22, 2017

WEB OF SCIENCETM
Citations

7
Last Week
0
Last month
0
Citations as of Jun 29, 2017

Page view(s)

35
Last Week
4
Last month
Checked on Jun 25, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.