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

Towards Global Solutions for Nonconvex Two-Stage Stochastic Programs: A Polynomial Lower Approximation Approach

Zhong, Suhan & Cui, Ying & Nie, Jiawang. (2024). Towards Global Solutions for Nonconvex Two-Stage Stochastic Programs: A Polynomial Lower Approximation Approach. SIAM Journal on Optimization. 34. 3477-3505. 10.1137/23M1615516.

In Situ Answer Sentence Selection at Web-scale

Zhang, Zeyu & Vu, Thuy & Moschitti, Alessandro. (2024). In Situ Answer Sentence Selection at Web-scale. 4298-4302. 10.1145/3627673.3679946.

Analysis of a Class of Minimization Problems Lacking Lower Semicontinuity

Han, Shaoning & Cui, Ying & Pang, Jong-Shi. (2024). Analysis of a Class of Minimization Problems Lacking Lower Semicontinuity. Mathematics of Operations Research. 10.1287/moor.2023.0295.

Scenario Grouping and Decomposition Algorithms for Chance-Constrained Programs

Yan Deng, Huiwen Jia, Shabbir Ahmed, Jon Lee, Siqian Shen, “Scenario Grouping and Decomposition Algorithms for Chance-constrained Programs”, INFORMS Journal on Computing, 3(2), 757-773, 2020

Multi-armed bandit with sub-exponential rewards

Huiwen Jia, Cong Shi, Siqian Shen, “Multi-armed Bandit with Sub-exponential Reward”, Operations Research Letters, 49(5), 728-733, 202, 2021

Benders Cut Classification via Support Vector Machines for Solving Two-Stage Stochastic Programs

Huiwen Jia, Siqian Shen, “Benders Cut Classification via Support Vector Machines for Two-stage Stochastic Integer Program’’, INFORMS Journal on Optimization, 3(3), 278-297, 2021