Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/25678
Title: Genetic optimization of order scheduling with multiple uncertainties
Authors: Guo, ZX
Wong, WK 
Leung, SYS 
Fan, JT
Chan, SF
Keywords: Genetic algorithms
Order scheduling
Probability theory
Uncertain processing time
Issue Date: 2008
Publisher: Pergamon Press
Source: Expert systems with applications, 2008, v. 35, no. 4, p. 1788-1801 How to cite?
Journal: Expert systems with applications 
Abstract: In this paper, the order scheduling problem at the factory level, aiming at scheduling the production processes of each production order to different assembly lines is investigated. Various uncertainties, including uncertain processing time, uncertain orders and uncertain arrival times, are considered and described as random variables. A mathematical model for this order scheduling problem is presented with the objectives of maximizing the total satisfaction level of all orders and minimizing their total throughput time. Uncertain completion time and beginning time of production process are derived firstly by using probability theory. A genetic algorithm, in which the representation with variable length of sub-chromosome is presented, is developed to generate the optimal order scheduling solution. Experiments are conducted to validate the proposed algorithm by using real-world production data. The experimental results show the effectiveness of the proposed algorithm.
URI: http://hdl.handle.net/10397/25678
ISSN: 0957-4174
EISSN: 1873-6793
DOI: 10.1016/j.eswa.2007.08.058
Appears in Collections:Journal/Magazine Article

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

SCOPUSTM   
Citations

34
Last Week
1
Last month
0
Citations as of Nov 10, 2017

WEB OF SCIENCETM
Citations

27
Last Week
0
Last month
0
Citations as of Nov 16, 2017

Page view(s)

51
Last Week
0
Last month
Checked on Nov 13, 2017

Google ScholarTM

Check

Altmetric



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