2023 AIChE Annual Meeting

Session: Data-driven optimization

Chair

Cremaschi, S., Auburn University

Co-Chair

Kwon, J., Texas A&M University

Presentations

03:30 PM

(430a) Hierarchical Planning-Scheduling-Control - Is Derivative-Free Optimization All You Need?

03:55 PM

(430b) Data-Driven Optimization of Highly Constrained Oil Recovery Processes Using Neural Network Surrogate Models and Classification Based Implicit Constraint Handling Schemes

04:20 PM

(430c) A Bayesian Optimization Framework for Solving Generic Inverse Optimization Problems

04:45 PM

(430d) A Data-Driven Framework for the Design of Reactor Simulations: Exploiting Multiple Continuous Fidelities

05:10 PM

(430e) A Reinforcement Learning Strategy with Recurrent Neural Networks for Optimal Scheduling of Job-Shop Batch Chemical Plants Under Uncertainty

05:35 PM

(430f) Decision-Focused Learning of Constraint Parameters with Feasibility Guarantee