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a superlinear interior points algorithm for engineering design optimizationWe present a quasi-Newton interior points algorithm for nonlinear constrained optimization. It is based on a general approach consisting of the iterative solution in the primal and dual spaces of the equalities in Karush-Kuhn-Tucker optimality conditions. This is done in such a way to have primal and dual feasibility at each iteration, which ensures satisfaction of those optimality conditions at the limit points. This approach is very strong and efficient, since at each iteration it only requires the solution of two linear systems with the same matrix, instead of quadratic programming subproblems. It is also particularly appropriate for engineering design optimization inasmuch at each iteration a feasible design is obtained. The present algorithm uses a quasi-Newton approximation of the second derivative of the Lagrangian function in order to have superlinear asymptotic convergence. We discuss theoretical aspects of the algorithm and its computer implementation.
Document ID
Document Type
Conference Paper
Herskovits, J.
(Universidade Federal do Rio de Janeiro Brazil)
Asquier, J.
(Aerospatiale Cannes, France)
Date Acquired
August 16, 2013
Publication Date
January 1, 1990
Publication Information
Publication: NASA. Langley Research Center, The Third Air Force(NASA Symposium on Recent Advances in Multidisciplinary Analysis and Optimization
Subject Category
Distribution Limits
Work of the US Gov. Public Use Permitted.

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