Research
IEOR researchers investigate the latest mathematical tools, approaches, and methodologies to make new theoretical discoveries and innovations that touch nearly every industry, making them more efficient and profitable in areas such as supply chain, logistics, manufacturing, data science, energy systems, robotics, and management.
Selected Publications
Gradient-Based Simulation Optimization Algorithms via Multi-Resolution System Approximations
Xu, Jingxu & Zheng, Zeyu. (2023). Gradient-Based Simulation Optimization Algorithms via Multi-Resolution System Approximations. INFORMS Journal on Computing. 35. 10.1287/ijoc.2023.1279.
A Doubly Stochastic Simulator with Applications in Arrivals Modeling and Simulation
Yufeng, Zheng & Zheng, Zeyu. (2020). Doubly Stochastic Generative Arrivals Modeling.
A Breakpoints Based Method for the Maximum Diversity and Dispersion Problems
Hochbaum, D. S., Liu, Z., & Goldschmidt, O. (2023). A Breakpoints Based Method for the Maximum Diversity and Dispersion Problems. In Proceedings of the SIAM Conference on Applied and Computational Discrete Algorithms (ACDA23) (pp. 189-200). Society for Industrial and Applied Mathematics. https://doi.org/10.1137/1.9781611977714.17
Mean-Field Controls with Q-Learning for Cooperative MARL: Convergence and Complexity Analysis
Interbank lending with benchmark rates: Pareto optima for a class of singular control games
, , . Interbank lending with benchmark rates: Pareto optima for a class of singular control games. Mathematical Finance. 2021; 31: 1357– 1393. https://doi.org/10.1111/mafi.12325