论文标题
多项式时间不可行的内点弧搜索算法用于凸优化
A polynomial time infeasible interior-point arc-search algorithm for convex optimization
论文作者
论文摘要
本文提出了使用Arc-Search Techniques的凸优化问题的不可行的内点算法。所提出的算法同时选择中心参数和步长，旨在优化每种迭代中的性能。提供了弧搜索的分析公式，以使Arc-Search方法非常有效。证明了算法的收敛性，并建立了算法的多项式结合。初步数值测试结果表明该算法是有效的。
This paper proposes an infeasible interior-point algorithm for the convex optimization problem using arc-search techniques. The proposed algorithm simultaneously selects the centering parameter and the step size, aiming at optimizing the performance in every iteration. Analytic formulas for the arc-search are provided to make the arc-search method very efficient. The convergence of the algorithm is proved and a polynomial bound of the algorithm is established. The preliminary numerical test results indicate that the algorithm is efficient and effective.
