In this paper, we deal with a polynomial primal-dual interior-point algorithm for solving convex quadratic programming based on a new parametric kernel function with an exponential barrier term. The proposed kernel function is not logarithmic and not self-regular. We analyze a class of large and small-update versions which are based on our new kernel function. The complexity obtained generalizes the result given by Bai et al. This result is the first to reach this goal. Finally, some numerical results are provided to show the efficiency of the proposed algorithm and to compare it with an available method.

中文翻译：

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基于新参数核函数的凸二次规划原对偶内点算法

在本文中，我们基于具有指数障碍项的新参数核函数来处理用于求解凸二次规划的多项式原始对偶内点算法。建议的核函数不是对数的，也不是自规则的。我们分析了一类基于我们新内核函数的大更新和小更新版本。获得的复杂性概括了 Bai 等人给出的结果。这个结果是第一个达到这个目标的。最后，提供了一些数值结果来表明所提出算法的效率，并将其与现有方法进行比较。