2022 Annual Meeting

Session: Data-driven optimization

Chair

Matthew Stuber, University of Connecticut

Co-Chair

Presentations

12:30 PM

(624a) Branch-and-Model: A Derivative-Free Global Optimization Algorithm
Nikolaos Sahinidis, Kaiwen Ma, Luis Miguel Rios, Atharv Bhosekar, Sreekanth Rajagopalan

12:49 PM

(624b) Data-Driven Coordination in Enterprise-Wide Optimization
Damien van de Berg, Nilay Shah, Antonio del Rio Chanona, Panagiotis Petsagkourakis

01:08 PM

(624c) A Surrogate-Based Framework for Feasibility Analysis and Optimization of Expensive Simulations
Huayu Tian, Marianthi Ierapetritou

01:27 PM

(624d) Data-Efficient Automated Tuning of Generic Control Structures Using Adversarially Robust Bayesian Optimization
Georgios Makrygiorgos, Joel Paulson, Ali Mesbah

01:46 PM

(624e) Accelerating Multiscale Global Optimization through Reduced Bayesian Optimization
Noah J. Wichrowski, Georgios Psarellis, Anastasia Georgiou, Juan Bello-Rivas, Felix Dietrich, Jonathan Hauenstein, Ioannis G. Kevrekidis

02:05 PM

(624f) Exploiting High-Throughput Experiments in Bayesian Optimization
Victor Zavala, Leonardo Gonzalez

02:24 PM

(624g) Snake: Bayesian Optimization Via Pathwise Exploration
Jose Pablo Folch, Shiqiang Zhang, Robert M. Lee, Behrang Shafei, David Walz, Calvin Tsay, Mark van der Wilk, Ruth Misener

02:43 PM

(624h) Optimization Under Uncertainty with Bayesian Hybrid Models
Alexander Dowling, Kyla Jones, Elvis Eugene, Jialu Wang