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

翻译：在这项工作中,介绍了一个高效的优化产量战略,其中含有不确定和决定性的优化变数。基于梯度的适应性牛顿-蒙特卡洛方法被修改,这样它就可以用(不确定参数)和没有(确定参数)分析梯度信息来处理变量。这一混合战略与衍生物自由方法进行了数字比较。