Data-driven Optimization

Relevant Publications

1. Black-Box Global Optimization
   • Data-driven Spatial Branch-and-bound Algorithm for Box-constrained Simulation-based Optimization
   • Managing Uncertainty in Data-Driven Simulation-Based Optimization
   • Machine learning-based surrogate modeling for data-driven optimization: a comparison of subset selection for regression techniques
   • Optimization of black-box problems using Smolyak grids and polynomial approximations
   • Global optimization of grey-box computational systems using surrogate functions and application to highly constrained oil-field operations
   • Optimal design of energy systems using constrained grey-box multi-objective optimization
   • Teaching data-analytics through process design
   • Dimensionality reduction for production optimization using polynomial approximations
   • ARGONAUT: AlgoRithms for Global Optimization of coNstrAined grey-box compUTational problems
   • Global Optimization Advances in Mixed-Integer Nonlinear Programming, MINLP, and Constrained Derivative-Free Optimization, CDFO
   
   
2. Feasibility analysis
   • Methods and Tools for Design Space Indentification in Pharmaceutical Development
   • Feasibility analysis of black-box processes using an adaptive sampling kriging-based method
   • Design Space of pharmaceutical processes using data-driven based methods
   
   
3. Uncertainty in Data-driven Optimization
   • Managing Uncertainty in Data-Driven Simulation-Based Optimization