EXPLOITING VISUAL OBSERVATIONS FOR EFFICIENT WORKFLOW SCHEDULING IN PRODUCTION ENVIRONMENTS

Anastasios Doulamis

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.

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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