Stable interior-point method for convex quadratic programming with\n strict error bounds

2017/11/04 by Martin Neuenhofen, Neuenhofen, Martin, Stefania Bellavia +1
Computer Science · Mathematics · #Advanced Optimization Algorithms Research #FOS: Mathematics #Matrix Theory and Algorithms #Optimization and Control (math.OC) #Optimization and Variational Analysis

paper · pdf · doi:10.48550/arxiv.1711.01418

openalex publication_date 2017/11/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We present a short step interior point method for solving a class of\nnonlinear programming problems with quadratic objective function. Convex\nquadratic programming problems can be reformulated as problems in this class.\nThe method is shown to have weak polynomial time complexity. A complete proof\nof the numerical stability of the method is provided. No requirements on\nfeasibility, row-rank of the constraint Jacobian, strict complementarity, or\nconditioning of the problem are made. Infeasible problems are solved to an\noptimal interior least-squares solution.\n

Citations

• Numerical optimization

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