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Self-Regularity : A New Paradigm for Primal-Dual Interior-Point Algorithms /
Research on interior-point methods (IPMs) has dominated the field of mathematical programming for the last two decades. Two contrasting approaches in the analysis and implementation of IPMs are the so-called small-update and large-update methods, although, until now, there has been a notorious gap b...
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| Autres auteurs: | , |
| Format: | Électronique eBook |
| Langue: | Inglés |
| Publié: |
Oxford :
Princeton University Press,
2002.
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| Collection: | Book collections on Project MUSE.
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| Sujets: | |
| Accès en ligne: | Texto completo |
| Résumé: | Research on interior-point methods (IPMs) has dominated the field of mathematical programming for the last two decades. Two contrasting approaches in the analysis and implementation of IPMs are the so-called small-update and large-update methods, although, until now, there has been a notorious gap between the theory and practical performance of these two strategies. This book comes close to bridging that gap, presenting a new framework for the theory of primal-dual IPMs based on the notion of the self-regularity of a function. The authors deal with linear optimization, nonlinear complementarity. |
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| Description matérielle: | 1 online resource: illustrations |
| ISBN: | 9781400825134 |