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In this work an efficient strategy for yield optimization with uncertain anddeterministic optimization variables is presented. The gradient based adaptiveNewton-Monte Carlo method is modified, such that it can handle variables with(uncertain parameters) and without (deterministic parameters) analyticalgradient information. This mixed strategy is numerically compared to derivativefree approaches.

Efficient yield optimization with limited gradient information