2021 Annual Meeting

Session: Data-driven optimization

Co-Chairs

Petsagkourakis, P., University College London
Bhosekar, A., Rutgers University

Presentations

12:30 PM

(476a) On the Use of Data Analytics Technology to Replace Dual Problems and Improve Decomposition Algorithms for Global Optimization Using Cutting Plane Approximations

12:49 PM

(476b) Deep Neural Network As Surrogates for Intractable Constraints and Problem Dimension Reduction: Security Constrained AC Optimal Power Flow

01:08 PM

(476c) Optimization of Fischer-Tropsch Microchannel Reactor Using Computational Fluid Dynamics and Transfer-Learned Bayesian Optimization.

01:27 PM

(476d) Computations and Optimization for Catalysts Under Dynamic Operation

02:05 PM

(476f) Digitalizing the Process Industries Via Surrogate Optimization

02:24 PM

(476g) Integration of Planning and Scheduling Using Data-Driven Feasibility Analysis

02:43 PM

(476h) Training and Reformulating Neural Network Surrogate Models for Optimization