Stochastic Modeling and Simulation Research

Faculty

Risk and uncertainty is inherent in all real-world systems, and understanding its impact is essential in performance analysis and optimization. Researchers in the IEOR Department at UC Berkeley are developing stochastic models and simulations for applications ranging from call centers to cloud computing, as well as expanding fundamental theory in areas such as stochastic control, semi-Martingale and filtration expansions, the economics of queueing systems, and design of simulation experiments.

Anil Aswani

Associate Professor

Xin Guo

Professor

Rhonda Righter

Professor
Head Graduate Advisor

Zeyu Zheng

Assistant Professor

Selected Publications

Simulating Nonstationary Spatio-Temporal Poisson Processes using the Inversion Method

Zhang, Haoting and Zheng, Zeyu, Simulating Nonstationary Spatio-Temporal Poisson Processes using the Inversion Method (July 27, 2020). Available at SSRN: https://ssrn.com/abstract=3661101 or http://dx.doi.org/10.2139/ssrn.3661101

Estimation and Inference for Non-Stationary Arrival Models with a Linear Trend

P. W. Glynn and Z. Zheng, “Estimation and Inference for Non-Stationary Arrival Models with a Linear Trend,” 2019 Winter Simulation Conference (WSC), National Harbor, MD, USA, 2019, pp. 3764-3773, doi: 10.1109/WSC40007.2019.9004779.

Accommodating New Flights into an Existing Airline Flight Schedule

Ozge Safak, Alper Atamturk and M. Selim Akturk. Accommodating New Flights into an Existing Airline Flight Schedule. Transportation Research Part C 104, 265-286, 2019. https://www.sciencedirect.com/science/article/abs/pii/S0968090X18315602?via%3Dihub.

Simulation and Real-World Evaluation of Attack Detection Schemes

M. Porter, A. Joshi, P. Hespanhol, A. Aswani, M. Johnson-Roberson, and R. Vasudevan (2019), Simulation and real-world evaluation of attack detection schemes, In Proceedings of the American Control Conference.

A scalable approach to enhancing stochastic kriging with Gradients

Haojun Huo; Xiaowei Zhang; Zeyu Zheng. “A scalable approach to enhancing stochastic kriging with Gradients”. Proceedings of the Winter Simulation Conference.

Approximating Systems Fed by Poisson Processes with Rapidly Changing Arrival Rates

Zeyu Zheng, Harsha Honnappa, Peter W. Glynn. “Approximating Systems Fed by Poisson Processes with Rapidly Changing Arrival Rates“. Operations Research

Stochastic Comparison of Discounted Rewards

The Stochastic Sequential Assignment Problem with Arrivals

R. Righter, “The Stochastic Sequential Assignment Problem with Arrivals,” Probability in the Engineering and Informational Sciences, 2011.

Optimal Production Policies with Multistage Stochastic Leadtimes

J.-H. Kim, H.-S. Ahn and R. Righter, “Optimal Production Policies with Multistage Stochastic Leadtimes,” Probability in the Engineering and Informational Sciences, vol. 23, pp. 515-543, 2009.

A constrained non-linear regular-singular stochastic control problem, with applications

X. Guo, J. Liu, and X. Y. Zhou. A constrained non-linear regular-singular stochastic control problem, with applications, Stochastic Processes and their Applications, 109(2):167-187, 2004.