Abstract
Large and sparse convex quadratic programming problems are often generated in the course of solving large-scale optimization problems. An important class of these problems has the property that only a small number of constraints are at their bounds at a solution. We describe an implementation of a range-space method designed for efficient solution of these small-active-set problems. The implementation is oriented toward the application area of multidimensional data fitting subject to constraints. Test results are presented for several data-fitting problems.
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Communicated by O. L. Mangasarian
The authors are indebted to the referees for several valuable contributions
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Frank, P.D., Healy, M.J. & Mastro, R.A. A range-space implementation for large quadratic programs with small active sets. J Optim Theory Appl 69, 109–127 (1991). https://doi.org/10.1007/BF00940463
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DOI: https://doi.org/10.1007/BF00940463