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. Attached Files Name Description MIMEType Size Downloads Title Minimizing bounded uncertainty impact on scheduling with earliest start and due-date constraints via interval computation Author(s) Hossny, Ahmad Nahavandi, Saeid orcid.org/0000-0002-0360-5270 Creighton, Douglas orcid.org/0000-0002-9217-1231 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 Collections: Institute for Intelligent Systems Research and Innovation (IISRI) GTP Research   Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Tue, 05 Mar 2013, 14:55:56 EST Wed, 05 Jun 2013, 15:28:33 EST Wed, 05 Jun 2013, 15:46:48 EST Wed, 05 Jun 2013, 15:48:20 EST Wed, 12 Jun 2013, 10:08:08 EST Wed, 02 Jul 2014, 16:01:09 EST Mon, 19 Jan 2015, 11:58:53 EST Fri, 06 Feb 2015, 11:06:58 EST Mon, 12 Oct 2015, 15:15:21 EST Wed, 14 Oct 2015, 13:26:25 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 631 Abstract Views, 4 File Downloads  -  Detailed Statistics Created: Tue, 05 Mar 2013, 14:55:56 EST

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