Abstract | ||
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Methods are developed and analyzed for estimating the distance to a local minimizer of a nonlinear programming problem. One estimate, based on the solution of a constrained convex quadratic program, can be used when strict complementary slackness and the second-order sufficient optimality conditions hold. A second estimate, based on the solution of an unconstrained nonconvex, nonsmooth optimization problem, is valid even when strict complementary slackness is violated. Both estimates are valid in a neighborhood of a local minimizer. An active set algorithm is developed for computing a stationary point of the nonsmooth error estimator. Each iteration of the algorithm requires the solution of a symmetric, positive semidefinite linear system, followed by a line search. Convergence is achieved in a finite number of iterations. The error bounds are based on stability properties for nonlinear programs. The theory is illustrated by some numerical examples. |
Year | DOI | Venue |
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2014 | 10.1007/s10898-014-0186-y | Journal of Global Optimization |
Keywords | Field | DocType |
Error bounds,KKT conditions,Active set algorithm,Nonconvex quadratic programming,Nonlinear programming | Mathematical optimization,Active set method,Linear system,Mathematical analysis,Nonlinear programming,Line search,Quadratic programming,Karush–Kuhn–Tucker conditions,Optimization problem,Mathematics,Estimator | Journal |
Volume | Issue | ISSN |
59 | 2-3 | 0925-5001 |
Citations | PageRank | References |
2 | 0.52 | 8 |
Authors | ||
2 |
Name | Order | Citations | PageRank |
---|---|---|---|
William W. Hager | 1 | 1603 | 214.67 |
Delphine Mico-Umutesi | 2 | 2 | 0.52 |