Proactive Algorithms for Scheduling with Probabilistic Durations
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. 1
Cite
Text
Beck and Wilson. "Proactive Algorithms for Scheduling with Probabilistic Durations." International Joint Conference on Artificial Intelligence, 2005.Markdown
[Beck and Wilson. "Proactive Algorithms for Scheduling with Probabilistic Durations." International Joint Conference on Artificial Intelligence, 2005.](https://mlanthology.org/ijcai/2005/beck2005ijcai-proactive/)BibTeX
@inproceedings{beck2005ijcai-proactive,
title = {{Proactive Algorithms for Scheduling with Probabilistic Durations}},
author = {Beck, J. Christopher and Wilson, Nic},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2005},
pages = {1201-1206},
url = {https://mlanthology.org/ijcai/2005/beck2005ijcai-proactive/}
}