Stochastic Modeling and Simulation Research
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.
E. Hyytiä and R. Righter, “Performance degradation in parallel-server systems with shared resources and lack of coordination,” Performance Evaluation, to appear, 2021. (Extended version of the Valuetools paper) https://doi.org/10.1016/j.peva.2021.102260
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
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.
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.
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.
Haojun Huo; Xiaowei Zhang; Zeyu Zheng. “A scalable approach to enhancing stochastic kriging with Gradients”. Proceedings of the Winter Simulation Conference.
Zeyu Zheng, Harsha Honnappa, Peter W. Glynn. “Approximating Systems Fed by Poisson Processes with Rapidly Changing Arrival Rates“. Operations Research