Simulation Optimization

Track Coordinators: Ilya O. Ryzhov, University of Maryland & Sujin Kim, National University of Singapore

The Simulation Optimization track is interested in papers on both theoretical and applied aspects of simulation optimization. In particular, it welcomes papers with methodological elements, e.g., analyzing properties of specific simulation models that lead to new or improved optimization techniques, or developing new computational algorithms for decision-making under uncertainty spanning multiple areas of application. It also welcomes papers on specific applications from areas such as healthcare, network applications, communications, financial engineering, and energy systems, where new or existing simulation optimization techniques are developed or applied.

• Methodological topics of interest include, but are not limited to, the following:
• Global and black-box optimization
• Discrete optimization
• Random search methods
• Sample average approximation
• Stochastic approximation methods