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Minimizing bounded uncertainty impact on scheduling with earliest start and due-date constraints via interval computation

Hossny, Ahmad, Nahavandi, Saeid and Creighton, Douglas 2012, Minimizing bounded uncertainty impact on scheduling with earliest start and due-date constraints via interval computation, in ETFA 2012 : Proceedings of the 2012 17th IEEE International Conference on Emerging Technologies & Factory Automation, IEEE, Piscataway, N.J., pp. 1-4.

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Title Minimizing bounded uncertainty impact on scheduling with earliest start and due-date constraints via interval computation
Author(s) Hossny, Ahmad
Nahavandi, Saeid
Creighton, Douglas
Conference name IEEE Emerging Technologies & Factory Automation. Conference (17th : 2012 : Krakow, Poland)
Conference location Krakow, Poland
Conference dates 17-21 Sep. 2012
Title of proceedings ETFA 2012 : Proceedings of the 2012 17th IEEE International Conference on Emerging Technologies & Factory Automation
Editor(s) [Unknown]
Publication date 2012
Conference series IEEE Emerging Technologies & Factory Automation Conference
Start page 1
End page 4
Total pages 4
Publisher IEEE
Place of publication Piscataway, N.J.
Summary Bounded uncertainty is a major challenge to real life scheduling as it increases the risk and cost depending on the objective function. Bounded uncertainty provides limited information about its nature. It provides only the upper and the lower bounds without information in between, in contrast to probability distributions and fuzzymembership functions. Bratley algorithm is usually used for scheduling with the constraints of earliest start and due-date. It is formulated as . The proposed research uses interval computation to minimize the impact of bounded uncertainty of processing times on Bratley’s algorithm. It minimizes the uncertainty of the estimate of the objective function. The proposed concept is to do the calculations on the interval values and approximate the end result instead of approximating each interval then doing numerical calculations. This methodology gives a more certain estimate of the objective function.
ISBN 9781467347372
Language eng
Field of Research 010101 Algebra and Number Theory
010206 Operations Research
Socio Economic Objective 910404 Productivity (excl. Public Sector)
HERDC Research category E1 Full written paper - refereed
Persistent URL http://hdl.handle.net/10536/DRO/DU:30050980

Document type: Conference Paper
Collection: Centre for Intelligent Systems Research
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