2023 AIChE Annual Meeting

Session: Advances in Optimization I

Co-Chairs

Kamil Khan, McMaster University
Can Li, Purdue University

Presentations

03:30 PM

(119a) A Branch-and-Bound Algorithm with Growing Datasets for Large-Scale Parameter Estimation
Alexander Mitsos, Susanne Sass, Dominik Bongartz, Ian H. Bell, Nikolay I. Nikolov, Angelos Tsoukalas

03:48 PM

(119b) Improving the Efficiency of Branch-and-Bound for Global Dynamic Optimization
Jason Ye, Joseph K. Scott

04:06 PM

(119c) Convexification of Nonconvex Compositions with Norms
Anatoliy Kuznetsov, Nikolaos Sahinidis

04:24 PM

(119d) LP-Based Preprocessing Algorithm and Tightening Constraints for Multiperiod Blend Scheduling Problems
Yingkai Song, Christos T. Maravelias

04:42 PM

(119e) Source Code Transformation for GPU-Enhanced Deterministic Global Optimization
Robert Gottlieb, Matthew Stuber

05:00 PM

(119f) Learning-Assisted AC Optimal Power Flow
Can Li, Gonzalo Constante-Flores

05:18 PM

(119g) Entropic Regularization for Wasserstein Distributionally Robust Chance-Constrained Process Optimization
Shu-Bo Yang, Zukui Li

05:36 PM

(119h) Advanced Solution Techniques for Event Constrained Programming
Daniel Ovalle, Joshua Pulsipher, Carl Laird, Ignacio Grossmann