Proactive algorithms for scheduling with probabilistic durations

Show simple item record Beck, J. Christopher Wilson, Nic 2020-11-17T13:24:54Z 2020-11-17T13:24:54Z 2005-07
dc.identifier.citation Beck, J.C., and Wilson, N. (2005) 'Proactive Algorithms for Scheduling with Probabilistic Durations', IJCAI'05: Proceedings of the 19th International Joint Conference on Artificial intelligence, Edinburgh, Scotland, 30 July - 05 August, pp. 1201-1206 en
dc.identifier.startpage 1201 en
dc.identifier.endpage 1206 en
dc.description.abstract Proactive scheduling seeks to generate high quality solutions despite execution time uncertainty. Building on work in [Beck and Wilson, 2004], we conduct an empirical study of a number of algorithms for the job shop scheduling problem with probabilistic durations. The main contributions of this paper are: the introduction and empirical analysis of a novel constraint-based search technique that can be applied beyond probabilistic scheduling problems, the introduction and empirical analysis of a number of deterministic filtering algorithms for probabilistic job shop scheduling, and the identification of a number of problem characteristics that contribute to algorithm performance. en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher International Joint Conferences on Artificial Intelligence (ICJAI) en
dc.rights © August 1, 2005 International Joint Conferences on Artificial Intelligence. All rights reserved. This publication, or parts thereof, may not be reproduced in any form without permission en
dc.subject Scheduling en
dc.subject Scheduling problem en
dc.subject Job shop scheduling problem en
dc.subject Deterministic scheduling algorithm en
dc.subject Classical scheduling formulation en
dc.subject Probabilistic problem en
dc.subject Constraint programming en
dc.title Proactive algorithms for scheduling with probabilistic durations en
dc.type Conference item en
dc.internal.authorcontactother Nic Wilson, Computer Science, University College Cork, Cork, Ireland. +353-21-490-3000 Email: en
dc.internal.availability Full text available en 2020-11-04T13:30:41Z
dc.description.version Accepted Version en
dc.internal.rssid 52485596
dc.contributor.funder Science Foundation Ireland en
dc.contributor.funder ILOG, USA en
dc.description.status Peer reviewed en
dc.internal.copyrightchecked No
dc.internal.licenseacceptance Yes en
dc.internal.conferencelocation Edinburgh, Scotland en
dc.internal.IRISemailaddress en
dc.relation.project info:eu-repo/grantAgreement/SFI/SFI Principal Investigator Programme (PI)/00/PI.1/C075/IE/Constraint Computation: Automation and Application/ en

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