Expected improvement based infill sampling for global robust optimization of constrained problems

A novel adaptive sampling scheme for efficient global robust optimization of constrained problems is proposed. The method addresses expensive to simulate black-box constrained problems affected by uncertainties for which only the bounds are known, while the probability distribution is not available. An iterative strategy for global robust...

Adaptive efficient global optimization of systems with independent components

We present a novel approach for efficient optimization of systems consisting of expensive to simulate components and relatively inexpensive system-level simulations. We consider the types of problem in which the components of the system problem are independent in the sense that they do not exchange coupling variables, however, design...

Global Robust Optimization of Computationally Expensive Systems: A Lavel Rotor Suspended by Fluid Film Bearings

Kriging based methods enable the deterministic and robust optimization of computationally expensive systems. With a limited amount of function evaluations the optima are found in an iterative process with expected improvement as infill sampling criteria. Outputs of computer models can be stochastic and/or the models do not always succeed to...