EXPLOITING VISUAL OBSERVATIONS FOR EFFICIENT WORKFLOW SCHEDULING IN PRODUCTION ENVIRONMENTS

Anastasios Doulamis

2011

Abstract

This paper proposes a new production scheduling algorithm that exploits (a) visual observations of industrial operations to estimate the actual completion times for tasks and (b) incremental graph partitioning-based clustering algorithms. The latter are implemented through an incremental implementation of the spectral clustering. Computer vision tools are applied to identify industrial operations via visual observations.

Paper Citation

in Harvard Style

Doulamis A. (2011). EXPLOITING VISUAL OBSERVATIONS FOR EFFICIENT WORKFLOW SCHEDULING IN PRODUCTION ENVIRONMENTS . In Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8425-40-9, pages 531-537. DOI: 10.5220/0003305905310537

in Bibtex Style

@conference{icaart11,
author={Anastasios Doulamis},
title={EXPLOITING VISUAL OBSERVATIONS FOR EFFICIENT WORKFLOW SCHEDULING IN PRODUCTION ENVIRONMENTS},
booktitle={Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2011},
pages={531-537},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003305905310537},
isbn={978-989-8425-40-9},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - EXPLOITING VISUAL OBSERVATIONS FOR EFFICIENT WORKFLOW SCHEDULING IN PRODUCTION ENVIRONMENTS
SN - 978-989-8425-40-9
AU - Doulamis A.
PY - 2011
SP - 531
EP - 537
DO - 10.5220/0003305905310537