5 papers
Machine Learning-assisted Dynamics-Constrained Day-Ahead Energy Scheduling
Mingjian Tuo, Xingpeng Li, Pascal Van Hentenryck
TThe rapid expansion of inverter-based resources, such as wind and solar power plants, will significantly diminish the presence of conventional synchronous generators in fu-ture po…
Inertia-Constrained Generation Scheduling: Sample Selection, Learning-Embedded Optimization Modeling, and Computational Enhancement
Mingjian Tuo, Fan Jiang, Xingpeng Li +1
Day-ahead generation scheduling is typically conducted by solv-ing security-constrained unit commitment (SCUC) problem. However, with fast-growing of inverter-based resources, grid…
Agentic AI for Scaling Diagnosis and Care in Neurodegenerative Disease
Andrew G. Breithaupt, Michael Weiner, Alice Tang +14
United States healthcare systems are struggling to meet the growing demand for neurological care, particularly in Alzheimer's disease and related dementias (ADRD). Generative AI bu…
A community-driven optimization framework for redrawing school attendance boundaries
Hongzhao Guan, Paul Riggins, Tyler Simko +8
The vast majority of US public school districts use school attendance boundaries to determine which student addresses are assigned to which schools. Existing work shows how redrawi…
Contextual Stochastic Optimization for Omnichannel Multi-Courier Order Fulfillment Under Delivery Time Uncertainty
Tinghan Ye, Sikai Cheng, Amira Hijazi +1
The paper studies a large-scale order fulfillment problem for a leading e-commerce company in the United States. The challenge involves selecting fulfillment centers and shipping c…