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A new preconditioning approach for an interior point‐proximal method of multipliers for linear and convex quadratic programming

机译：一种新的线性和凸二次编程乘法器内部点近端方法的新预处理方法

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Luca Bergamaschi; Jacek Gondzio; Ángeles Martínez; John W. Pearson; Spyridon Pougkakiotis;
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1. Dynamic Non-diagonal Regularization in Interior Point Methods for Linear and Convex Quadratic Programming [J] . Pougkakiotis Spyridon, Gondzio Jacek Journal of Optimization Theory and Applications . 2019,第3期

机译：线性和凸二次编程内点方法中的动态非对角线规则
2. On weighted linear least-squares problems related to interior methods for convex quadratic programming [J] . Forsgren A., Sporre G. SIAM Journal on Matrix Analysis and Applications . 2001,第1期

机译：与凸二次规划的内部方法有关的加权线性最小二乘问题
3. Stability and Accuracy of Inexact Interior Point Methods for Convex Quadratic Programming [J] . Morini Benedetta, Simoncini Valeria Journal of Optimization Theory and Applications . 2017,第2期

机译：凸二次编程不精确内点方法的稳定性和准确性
4. On extending kernel-based interior point algorithms for linear programming to convex quadratic second-order cone programming [C] . Yanfang Li, Xibo Duan, Jia Gu International Conference on Natural Computation;International Conference on Fuzzy Systems and Knowledge Discovery . 2015

机译：关于将基于线性规划的基于内核的内点算法扩展到凸二次二次锥编程
5. Interior algorithms for linear, quadratic, and linearly constrained convex programming [D] . Ye, Yinyu. 1988

机译：用于线性，二次和线性约束凸规划的内部算法
6. Conic Sampling: An Efficient Method for Solving Linear and Quadratic Programming by Randomly Linking Constraints within the Interior [O] . Oliver Serang -1

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7. Inexact Interior-Point Methods for Large Scale Linear and Convex Quadratic Semidefinite Programming [O] . LI LU 2010

机译：大规模线性和凸二次半定规划的不精确内点方法

A new preconditioning approach for an interior point‐proximal method of multipliers for linear and convex quadratic programming

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