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SQP Methods for Nonlinear Optimization
Elizabeth Wong
UCSD
Abstract:
We present a sequential quadratic programming (SQP) algorithm for nonlinear optimization. We give a brief overview of SQP methods in general and then describe an active-set method based on inertia control for solving the convex quadratic subproblems. We also discuss the motivation behind this algorithm as well as its applications.
Tuesday, March 3, 2009
11:00AM AP&M 2402
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Randolph E. Bank
Philip E. Gill
Michael Holst
Administrative Contact:
[ Click to Send Email ]
Elizabeth Wong
UCSD
Abstract:
We present a sequential quadratic programming (SQP) algorithm for nonlinear optimization. We give a brief overview of SQP methods in general and then describe an active-set method based on inertia control for solving the convex quadratic subproblems. We also discuss the motivation behind this algorithm as well as its applications.
Tuesday, March 3, 2009
11:00AM AP&M 2402