Efficient global robust optimization of unconstrained problems affected by parametric uncertainties

A novel technique for efficient global robust optimization of problems affected by parametric uncertainties is proposed. The method is especially relevant to problems that are based on expensive computer simulations. The globally robust optimal design is obtained by searching for the best worst-case cost, which involves a nested min-max...

System robust optimization of ring resonator-based optical filters

Fabrication variations can have a detrimental effect on the performance of optical filters based on ring resonators. However, by using robust optimization these effects can be minimized and device yield can be significantly improved. This paper presents an efficient robust optimization technique for designing manufacturable optical filters based...

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...

Deterministic vs. robust design optimization using DEM-based metamodels

In design optimization of bulk handling equipment (BHE) we generally focus on the mean performance of the equipment. However, granular materials behave stochastic due to irregularities in particle shape and size which leads to stochastic performance of the equipment. To include the stochastic performance we propose robust metamodel-based...