The Applied Optimization Laboratory (AOL) focuses on v, with a particular focus on healthcare. AOL benefits from the computational infrastructure provided by HPCVL to test the tools it develops. Examples of application areas are cancer therapy, defibrillator location, and wind farm design.
Intensity-modulated radiation therapy (IMRT) is a method for treating cancer based on delivering beams of radiation to the tumour. AOL uses historical patient data and inverse optimization to quantify the importance of various conflicting objectives in IMRT and thus automate the time-consuming task of parameter tuning of IMRT optimization models . AOL is also developing optimization models which account for breathing motion uncertainty, resulting in better treatment plans for breast cancer . HPCVL plays an important role in this research, providing the substantial memory and storage capacity required for working with radiotherapy patient data.
Automated external defibrillators (AEDs) are life-saving portable devices used to deliver shock to cardiac arrest victims in order to reset the heart’s normal rhythm. AOL is creating optimization models for finding optimal AED locations, which is essential for providing victims with timely access to an AED and maximizing the chances of survival in a cardiac arrest emergency . HPCVL is used for testing novel large-scale AED deployment optimization models using real cardiac arrest data.
In energy, AOL focuses on developing models for finding the optimal placement of turbines in a wind farm, which is critical to the maximization of power production . HPCVL is used to evaluate the performance of optimized wind farm layouts for a variety wind direction scenarios.
 T. C. Y. Chan, T. Craig, T. Lee, M. B. Sharpe, “Generalized inverse multi-objective optimization with application to cancer therapy,” Operations Research, Vol. 62, pp. 680-695, 2014.
 T. C. Y. Chan, H. Mahmoudzadeh, T. Purdie, “A robust-CVaR optimization approach with application to breast cancer therapy,” European Journal of Operational Research, Vol. 238, pp. 876-885, 2014.
 T. C. Y. Chan, H. Li, G. Lebovic, S. K. Tang, J. Y. T. Chan, H. C. K. Cheng, L. J. Morrison, S. C. Brooks, “Identifying locations for public access defibrillators using mathematical optimization,” Circulation, Vol. 127, pp. 1801-1809, 2013.
 S. D. O. Turner, D. A. Romero, P. Y. Zhang, C. H. Amon, T. C. Y. Chan, “A new mathematical programming approach to optimize wind farm layouts,” Renewable Energy, Vol. 63, pp. 674-680, 2014.