A Predictor-Corrector Algorithm for Linear Optimization Based on a Specific Self-Regular Proximity Function
نویسندگان
چکیده
It is well known that the so-called first-order predictor-corrector methods working in a large neighborhood of the central path are among the most efficient interior-point methods (IPMs) for linear optimization (LO) problems. However, the best known iteration complexity of this type of methods is O (
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عنوان ژورنال:
- SIAM Journal on Optimization
دوره 15 شماره
صفحات -
تاریخ انتشار 2005