Sensitivity Analysis for Nonlinear Programming Using Penalty Methods.
Abstract
In the paper the author establishes a theoretical basis for using a penalty-function method to estimate sensitivity information (i.e., the partial derivatives) of a local solution and its associated Lagrange multipliers of a large class of nonlinear programming problems with respect to a general parametric variation in the problem functions. The local solution is assumed to satisfy the second order sufficient conditions for a strict minimum. Although theoretically valid for higher order derivatives, tha analysis concentrates on the estimation of the first order (first partial derivative) sensitivity information, which can be explicitly expressed in terms of the problem functions. For greater clarity, the results are given in terms of the mixed logarithmic-barrier quadratic-loss function. However, the approach is clearly applicable to any twice-differentiable penalty-function algorithm. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 07, 1973
- Accession Number
- AD0762549
Entities
People
- Anthony V. Fiacco
Organizations
- George Washington University