A Truncated SQP Algorithm for Large Scale Nonlinear Programming Problems

Paul T. Boggs,Anthony J. Kearsley,Jon W. Tolle

doi:10.1007/978-94-015-8330-5_5

A Truncated SQP Algorithm for Large Scale Nonlinear Programming Problems

Paul T. Boggs, Anthony J. Kearsley + Show 1 more

https://doi.org/10.1007/978-94-015-8330-5_5

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Publication Date: Jan 1, 1992

Citations: 8

Affiliation: National Institute of Standards and Technology, Rice University, University of North Carolina at Chapel Hill

#Large Scale Nonlinear Programming Problems #Merit Function + Show 8 more

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Abstract

We consider the inequality constrained nonlinear programming problem and an SQP algorithm for its solution. We are primarily concerned with two aspects of the general procedure, namely, the approximate solution of the quadratic program, and the need for an appropriate merit function. We first describe an (iterative) interior-point method for the quadratic programming subproblem that, no matter when it is terminated, yields a descent direction for a suggested new merit function. An algorithm based on ideas from trust-region and truncated Newton methods is suggested and some of our preliminary numerical results are discussed.

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