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.
Selected Publications
Partner with a Third-Party Delivery Service or Not? — a Prediction-and-Decision Tool for Restaurants Facing Takeout Demand Surges During a Pandemic
Jia, Huiwen and Shen, Siqian and Garcıa, Jorge Alberto Ramırez and Shi, Cong, Partner with a Third-Party Delivery Service or Not? — a Prediction-and-Decision Tool for Restaurants Facing Takeout Demand Surges During a Pandemic (November 18, 2020). Available at SSRN: https://ssrn.com/abstract=3734018 or http://dx.doi.org/10.2139/ssrn.3734018
A Shared Mobility Based Framework for Evacuation Planning and Operations under Forecast Uncertainty
Kati Moug, Huiwen Jia, Siqian Shen, “A Shared Mobility Based Framework for Evacuation Planning and Operations Under Demand Uncertainty “, IISE Transactions, 55(10), 971-984, 2023.
A survey on geocoding: algorithms and datasets for toponym resolution
Zhang, Zeyu & Bethard, Steven. (2024). A survey on geocoding: algorithms and datasets for toponym resolution. Language Resources and Evaluation. 1-22. 10.1007/s10579-024-09730-2.
Improving Toponym Resolution by Predicting Attributes to Constrain Geographical Ontology Entries
Zhang, Zeyu & Laparra, Egoitz & Bethard, Steven. (2024). Improving Toponym Resolution by Predicting Attributes to Constrain Geographical Ontology Entries. 35-44. 10.18653/v1/2024.naacl-short.3.
Solving Nonsmooth Nonconvex Compound Stochastic Programs with Applications to Risk Measure Minimization
Liu, Junyi & Cui, Ying & Pang, Jong-Shi. (2020). Solving Nonsmooth Nonconvex Compound Stochastic Programs with Applications to Risk Measure Minimization.
Matching queues with reneging: a product form solution
Castro, Francisco & Nazerzadeh, Hamid & Yan, Chiwei. (2020). Matching queues with reneging: a product form solution. Queueing Systems. 96. 10.1007/s11134-020-09662-y.
Risk Bounds and Calibration for a Smart Predict-then-Optimize Method
Liu, Heyuan & Grigas, Paul. (2021). Risk Bounds and Calibration for a Smart Predict-then-Optimize Method.