A Practical Algorithm for General Large Scale Nonlinear Optimization Problems
نویسندگان
چکیده
We provide an eeective and eecient implementation of a sequential quadratic programming (SQP) algorithm for the general large scale nonlinear programming problem. In this algorithm the quadratic programming subproblems are solved by an interior point method that can be prematurely halted by a trust region constraint. Numerous computational enhancements to improve the numerical performance are presented. These include a dynamic procedure for adjusting the merit function parameter and procedures for adjusting the trust region radius. Numerical results and comparisons are presented.
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ورودعنوان ژورنال:
- SIAM Journal on Optimization
دوره 9 شماره
صفحات -
تاریخ انتشار 1999