Trajectory-following methods for large-scale degenerate convex quadratic programming
Trajectory-following methods for large-scale degenerate convex quadratic programming
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DOI：
10.1007/s12532-012-0050-3
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发表时间：
2013-06-01
影响因子：
6.3
通讯作者：
Robinson, Daniel P.
中科院分区：
文献类型：
--
作者：
Gould, Nicholas I. M.;Orban, Dominique;Robinson, Daniel P.
研究凸二次规划的一类不可行路径跟踪方法。我们的方法被设计为有效地解决两个nondegerate和退化的问题，退化被理解为意味着严格互补的解决方案的失败。给出了算法的全局收敛性和迭代次数的多项式界。一个实现，CQP，可作为GALAHAD的一部分。我们说明了我们的方法的优势CUTEr和Maros-Meszaros测试集。
We consider a class of infeasible, path-following methods for convex quadratric programming. Our methods are designed to be effective for solving both nondegerate and degenerate problems, where degeneracy is understood to mean the failure of strict complementarity at a solution. Global convergence and a polynomial bound on the number of iterations required is given. An implementation, CQP, is available as part of GALAHAD. We illustrate the advantages of our approach on the CUTEr and Maros-Meszaros test sets.