A Sampling Based Approach for Proactive Project Scheduling with Time-Dependent Duration Uncertainty

Wen Song, Donghun Kang, Jie Zhang, Hui Xi

AAAI 2017 pp. 4985-4986

doi:10.1609/AAAI.V31I1.11100 /aaai/2017/song2017aaai-sampling/

Abstract

Most of the existing proactive scheduling approaches assume the durations of activities can be described by independent random variables that have no relation with time. We deal with the more challenging problem where the duration uncertainty is related to the scheduled time period. We propose a sampling based approach by extending the Consensus method from stochastic optimization. Experimental results show the effectiveness of our approach in solution quality and stability.

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Cite

Text

Song et al. "A Sampling Based Approach for Proactive Project Scheduling with Time-Dependent Duration Uncertainty." AAAI Conference on Artificial Intelligence, 2017. doi:10.1609/AAAI.V31I1.11100

Markdown

[Song et al. "A Sampling Based Approach for Proactive Project Scheduling with Time-Dependent Duration Uncertainty." AAAI Conference on Artificial Intelligence, 2017.](https://mlanthology.org/aaai/2017/song2017aaai-sampling/) doi:10.1609/AAAI.V31I1.11100

BibTeX

@inproceedings{song2017aaai-sampling,
  title     = {{A Sampling Based Approach for Proactive Project Scheduling with Time-Dependent Duration Uncertainty}},
  author    = {Song, Wen and Kang, Donghun and Zhang, Jie and Xi, Hui},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2017},
  pages     = {4985-4986},
  doi       = {10.1609/AAAI.V31I1.11100},
  url       = {https://mlanthology.org/aaai/2017/song2017aaai-sampling/}
}