598 Advances in Optimization with Surrogate and Mixed-Integer Models


Description:
Process Systems Engineering has been heavily rooted in our ability to formulate models and analyze data so as to make good decisions. This session thus invites papers that contemplate advances in the theory, methods and numerical algorithms for optimal decision-making. Whereas demonstration of the contributions via examples drawn from specific application contexts are encouraged, papers should define in mathematical terms the broader problem class in which the contribution is relevant. All classes of optimization problems are considered.

Sponsor:
Computers in Operations and Information Processing


Chair:
Joseph Scott
Assistant Professor
Clemson University
Chemical and Biomolecular Engineering
Clemson, SC
29634
Email: jks9@clemson.edu

Co-Chair:
M. M. Faruque Hasan
Texas A&M University
Artie McFerrin Department of Chemical Engineering
College Station, TX
77843
Email: hasan@tamu.edu


Papers:
598a
Towards Global Optimization on Low-Dimensional Surrogates Via Manifold Learning
Felix Dietrich, Johns Hopkins University; Logan R. Matthews, Princeton University; Dmitry Pozharskiy, Princeton University; Ioannis G. Kevrekidis, Johns Hopkins University
598b
On the Derivation of Piecewise Linear Continuous Approximating Functions
Lingxun Kong, University of Wisconsin-Madison; Christos T. Maravelias, University of Wisconsin-Madison
598c
Surrogate-Based Optimization Framework in Process Systems Engineering
Atharv Bhosekar, Rutgers, The State University of New Jersey; Lisia S Dias, Rutgers, The State University of New Jersey; Zilong Wang, Rutgers, The State University of New Jersey; Marianthi Ierapetritou, Rutgers, The State University of New Jersey
598d
Spatial Branch-and-Bound Optimization Using Surrogate Approximations
Jianyuan Zhai, Georgia Institute of Technology; Fani Boukouvala, Georgia Institute of Technology
598e
Reduced Space Formulation for Global Optimization with Artificial Neural Networks Embedded
Artur M. Schweidtmann, RWTH Aachen University; Alexander Mitsos, RWTH Aachen University
598f
Optimization of Data-Dependent Mixed-Integer Nonlinear Problems
Sun Hye Kim, Georgia Institute of Technology; Fani Boukouvala, Georgia Institute of Technology
598g
On Discretization Based Global Optimization for Mixed-Integer Bilinear Programs
Xin Cheng, Queen's University; Xiang Li, Queen's University
598h
Quadratic Cut Decomposition Method for Convex Mixed-Integer Nonlinear Programs
David E. Bernal, Carnegie Mellon University; Lijie Su, Northeastern University, China; Lixin Tang, Northeastern University; Ignacio E. Grossmann, Carnegie Mellon University
Abstract Submissions Closed
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