Interior-Point Methods for Nonconvex Nonlinear Programming: Filter Methods and Merit Functions
نویسندگان
چکیده
Recently, Fletcher and Leyffer proposed using filter methods instead of a merit function to control steplengths in a sequential quadratic programming algorithm. In this paper, we analyze possible ways to implement a filter-based approach in an interior-point algorithm. Extensive numerical testing shows that such an approach is more efficient than using a merit function alone.
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عنوان ژورنال:
- Comp. Opt. and Appl.
دوره 23 شماره
صفحات -
تاریخ انتشار 2002