Simulation & Optimization Research Group
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.
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.»
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.»
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.»
Predicitve Waste Management for SBB Train Stations
We develop a system to optimize the waste collection and disposal on SBB's train stations. The new system will use a container fill level sensor network, a novel waste accumulation forecasting algorithm, and state of the art methods for simulation-based tour-planning.
Data-driven decision support for intracranial aneurysms and hospital catering using Bayesian networks
Clinical decisions in medicine and management decisions in facility management are regularly made on the basis of little evidence or extrapolations and are also influenced by subjective and economic aspects. While data is generated exponentially in medicine due to increasing digitization, there is no framework for ...
Rüegg, Ramona; Schmid, Tamara; Hollenstein, Lukas; Müller, Nadina,
LWT - Food Science and Technology.
Available from: https://doi.org/10.1016/j.lwt.2022.113859
Gerber, Nicole; Hollenstein, Lukas,
2022(4), pp. 79-80.
Available from: https://doi.org/10.21256/zhaw-25448
Vorburger, Robert; Hollenstein, Lukas,
2021(2), pp. 5.
Available from: https://doi.org/10.21256/zhaw-23748
Gerber, Nicole; Hollenstein, Lukas; Krähenbühl, Andrea,
FM Perspektiven: FM Innovationen in HC digital, Wädenswil, 26. November 2021.
Krähenbühl, Andrea; Gerber, Nicole; Höhener, Rebecca; Hollenstein, Lukas,
2021(4), pp. 22-24.
Available from: https://doi.org/10.21256/zhaw-23063