Simulation & Optimization
Carry out experiments in the simulator, rather than in reality!
Why we simulate
Markets, company structures and processes are not only complex, but are also changing ever more rapidly. Shorter cycles require rapid redesign and adjustment of internal and external structures and dependencies.
Our applied research transfers the newest methods from theory to practice. This enables us to develop individual and innovative solutions with our partners.
We enable you to recognize potential for rationalization and quantify it more effectively. We also help you achieve better understanding and control of dynamic and complex processes. Your planning quality improves significantly as we support you in asking the correct questions.
Thanks to user-friendly simulation tools, you can easily change your system parameters whenever necessary. In this way you adopt the best possible solution to your problem efficiently and without risk.
Our Team
Lukas Hollenstein Head of Center for Simulation & Optimization
Understanding and simulating processes and creating benefits
Motivation
We all want to
- use resources efficiently
- avoid risks
- disentangle processes
- understand dependencies
- work out quantified (and qualified) bases for decisions
«We achieve your goals innovatively and sustainably at the interface of research and practice.»
Procedure
We support you by
- analyzing your complex processes and systems
- reducing intricate relationships to the essentials
- developing dynamic models
- visualizing processes
- using optimization methods
«We solve complex problems through simulation and optimization.»
Benefits
Your benefits from our projects:
- analysis of your current situation and recommendations for action
- simulation models to quantitatively support your decisions
- visualizations for a better understanding of processes
- tools to support strategic and operational planning and innovative solutions
«We experiment with you in the simulator to find a predictable and economically viable reality.»
Projects
Since 1991, the research group has implemented more than 300 projects in the fields of plant and mechanical engineering, the food and chemical industries, hospital logistics and medical technology, road and air traffic, people flow, services and the military. We are proud to present some of our reference projects.
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Bayes network analysis for data-driven decision support in hospital catering
Constantly rising costs in the healthcare sector require economic action without compromising the quality of care. Hospital catering is cost-intensive, but also very significant for patient satisfaction. In addition to purely economic optimization, numerous qualitative factors such as sustainability and employee ...
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Fighting bites with bytes: Promoting public health with crowdsourced tick prevention
Ticks are on the rise and transmit several infectious diseases, leading to serious illness or even death. The smartphone App “Zecke–Tick Prevention helps people, to remember the tick bite location and to check it for potential Lyme disease symptoms. In an interdisciplinary approach, ZHAW-scientists want to find out ...
Current publications
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2020.
The collaborative learning cellular automata density classification problem [ paper ].
In:
Proceedings of the 2020 International Symposium on Nonlinear Theory and its Applications.
International Symposium on Nonlinear Theory and its Applications (NOLTA), Okinawa, Japan, 16–19 November 2020.
pp. 268.
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Maiolo, Massimo ; Ulzega, Simone ; Gil, Manuel ; Anisimova, Maria ,
2020.
Accelerating phylogeny-aware alignment with indel evolution using short time Fourier transform .
NAR Genomics and Bioinformatics.
2(4),
pp. lqaa092.
Available from : https://doi.org/10.1093/nargab/lqaa092
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Miniussi, Myriam; Ott, Thomas ; Fellermann, Harold,
2020.
Impact of noise and network size in coupled maps with asymmetric influence amplification [ paper ].
In:
Proceedings of the NOLTA 2020 Conference.
2020 International Symposium on Nonlinear Theory and Its Applications (NOLTA2020), Online Conference, 16-19 November 2020.
pp. 282-285.
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Gygax, Gregory ; Füchslin, Rudolf Marcel ; Ott, Thomas ,
2020.
In:
Proceedings of the NOLTA 2020 Conference.
2020 International Symposium on Nonlinear Theory and Its Applications (NOLTA2020), Online Conference, 16-19 November 2020.
pp. 278-281.
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Gygax, Gregory ; Schüle, Martin ,
2020.
A hybrid deep learning approach for forecasting air temperature [ paper ].
In:
Schilling, Frank-Peter; Stadelmann, Thilo, eds. ,
Artificial Neural Networks in Pattern Recognition.
9th IAPR TC 3 Workshop on Artificial Neural Networks for Pattern Recognition (ANNPR'20), Winterthur, Switzerland, 2-4 September 2020.
Cham:
Springer.
pp. 235-246.
Lecture Notes in Computer Science ; 12294.
Available from : https://doi.org/10.1007/978-3-030-58309-5_19