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.

中文翻译：

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梯度信息有限的高效收率优化

在这项工作中，提出了具有不确定和确定性优化变量的有效的产量优化策略。对基于梯度的自适应牛顿-蒙特卡洛方法进行了修改，使其可以处理具有（不确定参数）和不具有（确定性参数）解析梯度信息的变量。将这种混合策略与无导数方法进行数值比较。