Title:
Combined use of ai techniques and simulation to support production scheduling: evidence from empirical research
Authors:
- Romeo Bandinelli
- Virginia Fani
Published in:
(2024). ECMS 2024, 38th Proceedings
Edited by: Daniel Grzonka, Natalia Rylko, Grazyna Suchacka, Vladimir Mityushev, European Council for Modelling and Simulation.
DOI: http://doi.org/10.7148/2024
ISSN: 2522-2422 (ONLINE)
ISSN: 2522-2414 (PRINT)
ISSN: 2522-2430 (CD-ROM)
ISBN: 978-3-937436-84-5
ISBN: 978-3-937436-83-8 (CD) Communications of the ECMS Volume 38, Issue 1, June 2024, Cracow, Poland June 4th – June 7th, 2024
DOI:
https://doi.org/10.7148/2024-0034
Citation format:
Romeo bandinelli, Virginia fani (2024). Combined Use Of Ai Techniques And Simulation To Support Production Scheduling: Evidence From Empirical Research, ECMS 2024, Proceedings Edited by: Daniel Grzonka, Natalia Rylko, Grazyna Suchacka, Vladimir Mityushev, European Council for Modelling and Simulation. doi:10.7148/2024-0034
Abstract:
This paper reports a literature review on the Artificial Intelligence (AI) techniques applied in the field of production planning and scheduling and explores the synergistic integration of AI with simulation for enhancing production scheduling. Leveraging Microsoft Project Bonsai and AnyLogic, we present a case study that demonstrates the effectiveness of AI-driven simulation models in optimizing scheduling tasks. Our research highlights the potential of combining AI with traditional simulation methods. The results offer insights into the practical applications and future potential of AI in industrial automation and production management.
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