Proactive algorithms for scheduling with probabilistic durations

Loading...
Thumbnail Image
Files
BeckWilson2005.pdf(149.93 KB)
Accepted version
Date
2005-07
Authors
Beck, J. Christopher
Wilson, Nic
Journal Title
Journal ISSN
Volume Title
Publisher
International Joint Conferences on Artificial Intelligence (ICJAI)
Published Version
Research Projects
Organizational Units
Journal Issue
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.
Description
Keywords
Scheduling , Scheduling problem , Job shop scheduling problem , Deterministic scheduling algorithm , Classical scheduling formulation , Probabilistic problem , Constraint programming
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
Copyright
© 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