Dimensionality reduction for production optimization using polynomial approximations

Computational Geosciences 2017

B. Beykal C.A. Floudas F. Boukouvala E. Gildin N. Sorek

The objective of this paper is to introduce a novel paradigm to reduce the computational effort in waterflooding global optimization problems while realizing smooth well control trajectories amenable for practical deployments in the field. In order to overcome the problems…

ARGONAUT: AlgoRithms for Global Optimization of coNstrAined grey-box compUTational problems

Optimization Letters 2016

F. Boukouvala C.A. Floudas

The algorithmic framework ARGONAUT is presented for the global optimization of general constrained grey-box problems. ARGONAUT incorporates variable selection, bounds tightening and constrained sampling techniques, in order to develop accurate surrogate representations of unknown equations, which are globally optimized. ARGONAUT…

Data‚ÄźDriven Mathematical Modeling and Global Optimization Framework for Entire Petrochemical Planning Operations

AIChE Journal 2016

J. Lie X. Xiao F. Boukouvala C.A. Floudas B. Zhao G. Du S. Xu H. Liu

In this work we develop a novel modeling and global optimization-based planning formulation, which predicts product yields and properties for all of the production units within a highly integrated refinery-petrochemical complex. Distillation is modeled using swing-cut theory, while data-based nonlinear…

Global Optimization Advances in Mixed-Integer Nonlinear Programming, MINLP, and Constrained Derivative-Free Optimization, CDFO

European Journal of Operational Research 2015

F. Boukouvala R. Misener C.A. Floudas

This manuscript reviews recent advances in deterministic global optimization for Mixed-Integer Nonlinear Programming (MINLP), as well as Constrained Derivative-Free Optimization (CDFO). This work provides a comprehensive and detailed literature review in terms of significant theoretical contributions, algorithmic developments, software implementations…