Advances in Nonlinear and Surrogate Optimization | AIChE

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Advances in Nonlinear and Surrogate Optimization

Chair(s)

Allman, A., University of Michigan

Co-chair(s)

Hasan, F., Texas A&M University

Optimization methods algorithms form the core tools for process operations and process systems engineering in general. The session invites papers in the general area of Process Systems Optimization. Topics on theory, algorithms and software for all classes of optimization problems are considered. Application papers offering insights into the interplay between optimization theory and practice are also encouraged.

Presentations

8:00 AM
(234a) New Measures for Shaping Trajectories in Dynamic Optimization
8:18 AM
(234b) An Implicit Function Formulation for Optimization of Discretized Index-1 Differential Algebraic Systems
8:36 AM
Break
8:54 AM
(234d) Learning to Initialize Generalized Benders Decomposition
9:12 AM
(234e) Global Convergence Analysis of Data-Driven Spatial Branch-and-Bound Algorithms
9:30 AM
(234f) Exploiting Grey-Box Hybrid Models in Constrained Bayesian Optimization Using a Smoothed Sample Average Approximation
9:48 AM
(234g) A Novel Surrogate-Based Derivative-Free Optimization Algorithm
10:06 AM
(234h) A Benders Decomposition Framework for the Optimization of Generalized Disjunctive Programming Problems with Ordered Boolean Variables

Topics 

Computing and Systems Engineering

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Pricing

Individuals

AIChE Pro Members $150.00
AIChE Emeritus Members $105.00
AIChE Graduate Student Members Free
AIChE Undergraduate Student Members Free
AIChE Explorer Members $225.00
Non-Members $225.00

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