A trust region method based on interior point techniques for nonlinear programming |
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| Authors: | Richard H. Byrd Jean Charles Gilbert Jorge Nocedal |
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| Affiliation: | (1) Computer Science Department, University of Colorado, Boulder CO 80309, USA, US;(2) INRIA Rocquencourt, B.P. 105, 78153 Le Chesnay Cedex, France, FR;(3) ECE Department, Northwestern University, Evanston Il 60208, USA, US |
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| Abstract: | ![]()
An algorithm for minimizing a nonlinear function subject to nonlinear inequality constraints is described. It applies sequential quadratic programming techniques to a sequence of barrier problems, and uses trust regions to ensure the robustness of the iteration and to allow the direct use of second order derivatives. This framework permits primal and primal-dual steps, but the paper focuses on the primal version of the new algorithm. An analysis of the convergence properties of this method is presented. Received: May 1996 / Accepted: August 18, 2000?Published online October 18, 2000 |
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| Keywords: | : constrained optimization – interior point method – large-scale optimization – nonlinear programming – primal method – primal-dual method – SQP iteration – barrier method – trust region method Mathematics Subject Classification (1991): 20E28, 20G40, 20C20 |
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