论文标题
推断的比例综合投影梯度方法进行圆锥优化
Extrapolated Proportional-Integral Projected Gradient Method for Conic Optimization
论文作者
论文摘要
圆锥优化是受圆锥约束的凸二次功能的最小化。我们引入了一种新型的一阶方法，用于圆锥优化，称为\ emph {外推优体投影梯度方法（XPIPG）}，自动检测到不可行。 XPIPG的迭代渐近地满足了一组原始的双重最优条件，或者产生原始或双重可口的证明。我们在模型预测控制中使用基准问题证明了XPIPG的应用。 XPIPG优于许多最先进的圆锥优化求解器，尤其是在解决大规模问题时。
Conic optimization is the minimization of a convex quadratic function subject to conic constraints. We introduce a novel first-order method for conic optimization, named \emph{extrapolated proportional-integral projected gradient method (xPIPG)}, that automatically detects infeasibility. The iterates of xPIPG either asymptotically satisfy a set of primal-dual optimality conditions, or generate a proof of primal or dual infeasibility. We demonstrate the application of xPIPG using benchmark problems in model predictive control. xPIPG outperforms many state-of-the-art conic optimization solvers, especially when solving large-scale problems.
