Theoretical and computational aspects of the optimal design centering, tolerancing, and tuning problem
Elijah Polak, Alberto L. Sangiovanni-Vincentelli · IEEE Transactions on Circuits and Systems · 1979
The optimal design centering, tolerancing, and tuning problem is transcribed into a mathematical programming problem of the formP_g: \min\{f(x)|\max_{\omega\in\Omega}\min_{\tau\in\Gamma} \zeta^{j}(x,\omega, \tau) \leq 0\} , x \geq 0, x, \omega, \tau \in R^{n},f: R^n \rightarrow R^1,\zeta: R^n \times R^n \times R^n \rightarrow R^1, continuously differentiable,\OmegaandTcompact subsets ofR^n,J=\{1, \cdots , p\}. A simplified form ofP_g,P: \min \{f(x) \Psi (x) \underset{=}{\triangle} \max_{omega\in \Omega \min_{\tau \in T} \zeta(x,\omega, \tau ) \leq 0 \}is discussed. It is shown that$\Psi(\cdot )is locally Lipschitz continuous but not continuously differentiable. Optimality conditions forPbased on the concept of generalized gradients are derived. An algorithm, consisting of a master outer approximations algorithm proposed by Gonzaga and Polak and of a new subalgorlthm for nondifferentiable problems of the formP_{i}: \min\{f(x)| \max_{\omega\in\Omega_i\} \min_{\tau \in T} \zeta (x, \omega, \tau ) \leq 0 \}, where\Omega_iis a discrete set, is presented. The subalgorlthm, an extension of Polak's method of feasible directions to nondifferentlable problems, is shown to converge under suitable assumptions. Moreover, the optimality function used in the subalgorithm is proven to satisfy a condition which guarantees that the overall algorithm converges.