论文标题
部分可观测时空混沌系统的无模型预测
Iteration Complexity of an Infeasible Interior Point Methods for Seconder-order Cone Programming and its Warmstarting
论文作者
论文摘要
本文研究了SECONDER ORDER CONE编程（SOCP）的不可行的内部方法（IPM）的最坏情况的迭代复杂性，与可行的IPM相比，它更方便。该方法研究了均质和自偶联模型以及Monteiro-Zhang搜索方向的基础。它最糟糕的情况是$ o \ weft（k^{1/2} \ log \ left（ε^{ - 1} \ right）\ right）$，以减少原始残留，双重残留和互补性差距，而$ε$，其中$ k $是$ k $的锥体约束数量。结果与可行IPM的最著名结果相同。还研究了加热剂改善复杂性结合的条件。
This paper studies the worst case iteration complexity of an infeasible interior point method (IPM) for seconder order cone programming (SOCP), which is more convenient for warmstarting compared with feasible IPMs. The method studied bases on the homogeneous and self-dual model and the Monteiro-Zhang family of searching directions. Its worst case iteration complexity is $O\left(k^{1/2}\log\left(ε^{-1}\right)\right)$, to reduce the primal residual, dual residual, and complementarity gap by a factor of $ε$, where $k$ is the number of cone constraints. The result is the same as the best known result for feasible IPMs. The condition under which warmstarting improves the complexity bound is also studied.
