loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Author: Norbert Gronau

Affiliation: University of Potsdam, Germany

Abstract: Modern process optimization approaches do build on various qualitative and quantitative tools, but are mainly limited to simple relations in different process perspectives like cost, time or stock. In this keynote a new approach is presented, which focuses on techniques of the area of Artificial Intelligence to capture complex relations within processes. Hence, a fundamental value increase is intended to be gained. Existing modeling techniques and languages serve as basic concepts and try to realize the junction of apparently contradictory approaches. This keynote therefore draws a vision of promising future process optimization techniques and presents an innovative contribution.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.145.63.136

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Gronau, N. (2017). A Visionary Way to Novel Process Optimization Techniques. In Proceedings of the Seventh International Symposium on Business Modeling and Software Design - BMSD; ISBN 978-989-758-238-7, SciTePress, pages 3-3. DOI: 10.5220/0006526700030003

@conference{bmsd17,
author={Norbert Gronau.},
title={A Visionary Way to Novel Process Optimization Techniques},
booktitle={Proceedings of the Seventh International Symposium on Business Modeling and Software Design - BMSD},
year={2017},
pages={3-3},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006526700030003},
isbn={978-989-758-238-7},
}

TY - CONF

JO - Proceedings of the Seventh International Symposium on Business Modeling and Software Design - BMSD
TI - A Visionary Way to Novel Process Optimization Techniques
SN - 978-989-758-238-7
AU - Gronau, N.
PY - 2017
SP - 3
EP - 3
DO - 10.5220/0006526700030003
PB - SciTePress