Advances in Optimization: Global, Uncertainty, Surrogate & Mixed-Integer Models I

Siirola, J. D., Sandia National Laboratories
Shao, Y., Georgia Institute of Technology
Zhang, Q., University of Minnesota
Tsay, C., The University of Texas at Austin
Maddala, J., West Virginia University
Castro, P. M., Faculdade de Ciências, Universidade de Lisboa

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.



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