Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
Interior path following primal-dual algorithms. Part II: Convex quadratic programming
Mathematical Programming: Series A and B
An algorithm for convex quadratic programming that requires O(n3.5L) arithmetic operations
Mathematics of Operations Research
An OL(n3) primal interior point algorithm for convex quadratic programming
Mathematical Programming: Series A and B
An interior point method for quadratic programs based on conjugate projected gradients
Computational Optimization and Applications
The Design and Analysis of Computer Algorithms
The Design and Analysis of Computer Algorithms
A New Algorithm for Solving Strictly Convex Quadratic Programs
SIAM Journal on Optimization
Numerical Methods for Unconstrained Optimization and Nonlinear Equations (Classics in Applied Mathematics, 16)
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We propose an exterior Newton method for strictlyconvex quadratic programming (QP)problems. This method is based on a dual formulation:a sequence of points is generated which monotonicallydecreases the dual objective function.We show that the generated sequenceconverges globally and quadratically to the solution (if the QPis feasible and certain nondegeneracy assumptions are satisfied). Measures for detecting infeasibility are provided. The major computation in each iteration is to solve a KKT-likesystem. Therefore, given an effective symmetricsparse linear solver, the proposed method is suitable for large sparseproblems. Preliminary numerical results are reported.