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On the solution of indefinite quadratic problems using an interior-point algorithm
Volume 3, Issue 4 (1992), pp. 474–496
Chi-Geun Han   Panos M. Pardalos   Yinyu Ye  

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https://doi.org/10.3233/INF-1992-3403
Pub. online: 1 January 1992      Type: Research Article     

Research supported in part by NSF Grant DDM-8922636 and the Iowa Business School Summer Grant.

Published
1 January 1992

Abstract

In this paper, we discuss computational aspects of an interior-point algorithm [1] for indefinite quadratic programming problems with box constraints. The algorithm finds a local minimizer by successively solving indefinite quadratic problems with an ellipsoid constraint. In addition, we present a sufficient condition for a local minimizer to be global, and we use this result to generate test problems with a known global solution. The proposed algorithm has been implemented on an IBM 3090 computer and tested on a variety of dense test problems, including problems with a known global optimizer.

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Keywords
nonconvex quadratic programming interior point algorithms computational testing

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INFORMATICA

  • Online ISSN: 1822-8844
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