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Abstract The first-order necessary conditions of optimality are extended to include information about robust design — cost insensitivity to model inaccuracies and changes in design specification, as well as the manufacturing tolerances treated in more traditional approaches. In these extended conditions, the Lagrangian is formulated as a tradeoff between cost and cost variability, where variability is measured as the flatness and curvature of the objective relative to local variations in design variables and constraints. During optimization these conditions allow cost and robustness to be considered simultaneously at each iteration.
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