Data-driven Process Systems Engineering Lab
Publications
Data-driven Spatial Branch-and-bound Algorithm for Box-constrained Simulation-based Optimization
Journal of Global Optimization 2021
The ability to use complex computer simulations in quantitative analysis and decision-making is highly desired in science and engineering, at the same rate as computation capabilities and first-principle knowledge advance. Due to the complexity of simulation models, direct embedding of…
Surrogate-Based Optimization for Mixed-Integer Nonlinear Problems
Computers & Chemical Engineering 2020
Simulation-based optimization using surrogate models enables decision-making through the exchange of data from high-fidelity models and development of approximations. Many chemical engineering optimization problems, such as process design and synthesis, rely on simulations and contain both discrete and continuous decision…
Computational Notebooks in Chemical Engineering Curricula
Chemical Engineering Education 2020
An integrated data-driven modeling & global optimization approach for multi-period nonlinear production planning problems
Computers & Chemical Engineering 2020
An integrated data-driven modeling & global optimization approach for multi-period nonlinear production planning problems
Computers & Chemical Engineering 2020
In this work, we present an integrated data-driven modeling and global optimization-based multi-period nonlinear production planning framework that is applied to a real-life refinery complex. The proposed multi-period framework significantly extends and improves previous works based on single-period planning formulation…
