Optimization and Algorithms Research
Optimization is in the center of every engineering discipline and every sector of the economy. Airlines and logistics companies run optimization algorithms to schedule their daily operations; power utilities rely on optimization to efficiently operate generators and renewable resources and distribute electricity; biotechnology firms search through massive genetic data using optimization to find new discoveries. UC Berkeley IEOR Department is at the forefront of optimization research. Our faculty and their students create new fields of optimization and push the boundaries in convex and nonconvex optimization, integer and combinatorial optimization to solve problems with massive data sets. Research activities are funded by NSF, DOE, DOD, ONR, and IBM Corporation.
Faculty
Selected Publications
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
An Optimization-and-Simulation Framework for Redesigning University Campus Bus System with Social Distancing
Gongyu Chen, Xinyu Fei, Huiwen Jia, Xian Yu, Siqian Shen, “The University of Michigan Implements a Hub-and-Spoke Design to Accommodate Social Distancing in the Campus Bus System under COVID Restrictions”, INFORMS Journal on Applied Analytics, 52(6):539-552, 2023
Online Learning and Pricing for Service Systems with Reusable Resources
Jia, Huiwen & Shi, Cong & Shen, Siqian. (2022). Online Learning and Pricing for Service Systems with Reusable Resources. Operations Research. 72. 10.1287/opre.2022.2381.
Auto- Train-Once: Controller Network Guided Automatic Network Pruning from Scratch
Wu, Xidong & Gao, Shangqian & Zhang, Zeyu & Li, Zhenzhen & Bao, Runxue & Zhang, Yanfu & Wang, Xiaoqian & Huang, Heng. (2024). Auto- Train-Once: Controller Network Guided Automatic Network Pruning from Scratch. 16163-16173. 10.1109/CVPR52733.2024.01530.
On the Softplus Penalty for Large-Scale Convex Optimization
Li, Meng & Grigas, Paul & Atamtürk, Alper. (2023). On the Softplus Penalty for Large-Scale Convex Optimization. Operations Research Letters. 51. 10.1016/j.orl.2023.10.015.