Christoph Waibel room EMPA
PhD Student tel +41 58 765 4120




2012: M.Sc. in Built Environment: Environmental Design and Engineering (University College London)
2010: Dipl.-Ing. in Architecture (University of Stuttgart)


2014 - present: PhD student at Empa / ETH Zürich
2012 - 2014: TÜV Rheinland ifes - Institute for Applied Energy Simulation, project engineer (Cologne)
2011: One to One GmbH, programmer and 3d constructor (Frankfurt am Main)
2006 - 2008: Student assistant architect in various firms (Stuttgart)

Research interests

  • Heuristic optimization
  • Meta-heuristics
  • Hyper-heuristics
  • Simulation-based optimization
  • Computational design strategies
  • Building energy simulation
  • Simplified building simulation models
  • Energy-efficient building and neighbourhood design


PhD: Hyper-Heuristic Framework in Urban Systems Optimization

A major share of global resource and energy consumption can be associated with cities. Considering the ongoing trends of urbanization and population growth it becomes evident that their evolution is a crucial keystone in tackling global environmental and economic challenges. It has been shown that cities and buildings are far from the ”efficiency possibility frontier” and could achieve much higher utility with less energy and resource input. One reason for inefficient designs can be found in the inherent complexity of the design process, which requires the expertise of multiple disciplines. The traditional approach to cope with this is to separate responsibilities and to exchange information in sequential steps. However, generating, processing and exchanging information is a costly practice and every change in design requires re-evaluation of other related disciplines. Thus, only a low degree of reciprocity is realized.

Holistic optimization methods may overcome this issue, as they can inform the design process by exploring vast numbers of design solutions across multiple performance criteria simultaneously. One of the practical challenges lies in the selection of appropriate optimization algorithms best suited to specific problem formulations. Hyper-heuristics deals with this by introducing a higher-level method for automatically selecting and tuning a tailored heuristic from a set of algorithmic operators. This research focuses on the development and application of a hyper-heuristic framework for multi-objective urban design, including building morphology and urban energy systems. Questions to be addressed using the hyper-heuristic optimization framework include the range and degree of multi-energy network connectivity within and across neighborhoods, the degree of densification for optimal demand and renewable energy generation, and the use of building standards (Passivhaus, nZEB, active house) in the context of a connected multi-energy-grid. Hyper-heuristic methods have the potential to change the overall design approach and enable holistic design and planning, where reciprocities between different disciplines and scales can be captured, thus leading to more efficient urban systems.




Conference proceedings

1. Waibel, C.*, Bystricky, L., Aytac, K., Evins, R., Carmeliet, J. (2017).
Validation of Grasshopper-based Fast Fluid Dynamics for Air Flow around Buildings in Early Design Stage.
In: 15th International Conference of the International Building Performance Simulation Association (IBPSA), BS 2017, San Francisco, USA, August 7th – 9th 2017. (Forthcoming).
2. Wortmann, T.*, Waibel, C.*, Nannicini, G., Evins, R., Schroepfer, T., Carmeliet, J. (2017).
Are Genetic Algorithms Really the Best Choice for Building Energy Optimization?
In: Symposium on Simulation for Architecture & Urban Design, SimAUD 2017, Toronto, Canada, May 22nd – 24th 2017 (Forthcoming).
3. Waibel, C.*, Evins, R., Carmeliet, J. (2016).
Using Interpolation to Generate Hourly Annual Solar Potential Profiles for Complex Geometries.
In: Building Simulation & Optimization, BSO 2016, Newcastle, United Kingdom, September 12th – 14th 2016.
4. Waibel, C.*, Evins, R., Carmeliet, J. (2016).
Holistic Optimization of Urban Morphology and District Energy Systems.
In: Sustainable Built Environment Conference, SBE16, Zurich, Switzerland, June 15th – 17th 2016.
5. Waibel, C.*, Evins, R. (2015).
Exploring the Use of Variable Mapping for Optimising Urban Morphologies.
In: 14th International Conference of the International Building Performance Simulation Association (IBPSA), BS 2015, Hyderabad, India, December 7th – 9th 2015.
6. Waibel, C.*, Ramallo-González, A.P., Evins, R., Carmeliet, J. (2015).
Reducing the Computing Time of Multi-Objective Building Optimisation using Self-Adaptive Sequential Model Assessment.
In: 14th International Conference of the International Building Performance Simulation Association (IBPSA), BS 2015, Hyderabad, India, December 7th – 9th 2015.
7. Hohmann, M.*, Waibel, C., Evins, R., Carmeliet, J. (2015).
Multi-objective optimization of the design and operation of an energy hub for the Empa campus.
In: Proceedings of International Conference CISBAT 2015 “Future Buildings and Districts – Sustainability from Nano to Urban Scale”, p. 591-596 Lausanne: LESO-PB, EPFL, 2015.
8. Waibel, C.* (2012).
Non-deterministic Shape Optimisation of Wind Cowls by applying Simulated Annealing and Fast Fluid Dynamics.
In: Proceedings of 2nd Conference: People and Buildings. Network for Comfort and Energy Use in Buildings (NCEUB), London, UK, September 2012.

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