Yaguang Yang

Arc-Search Techniques for Interior-Point Methods (eBook, ePUB)

• Format: ePub

Produktbeschreibung

This book discusses one of the most recent developments in interior-point methods, the arc-search techniques. Introducing these techniques result in an efficient interior-point algorithm with the lowest polynomial bound, which solves a long-standing issue of the interior-point methods in linear programming.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 316
• Erscheinungstermin: 26. November 2020
• Englisch
• ISBN-13: 9781000220339
• Artikelnr.: 60167577

Autorenporträt

Yaguang Yang received a BSc (1982) and a MSc (1985) from Huazhong University of Science and Technology, China. From 1985 to 1990, he was a lecturer at Zhejiang University in China. In 1996, he received his PhD from the Department of Electrical and Computer Engineering at the University of Maryland, College Park. He proposed and developed arc-search techniques for interior-point methods. He is currently with the US Nuclear Regulatory Commission.

Inhaltsangabe

Preface. SECTION I: LINE SEARCH INTERIOR
POINT METHODS FOR LINEAR PROGRAMMING. Introduction. A Potential
Reduction Algorithm for LP. Feasible Path
Following Algorithms for LP. Infeasible Interior
Point Method Algorithms for LP. SECTION II: ARC
SEARCH INTERIOR
POINT METHODS FOR LINEAR PROGRAMMING. A Feasible Arc
Search Algorithm for LP. A MTY
Type Infeasible Arc
Search Algorithm for LP. A Mehrotra
Type Infeasible Arc
Search Algorithm for LP. An O(¿nL) Infeasible Arc
Search Algorithms for LP. SECTION III:ARC
SEARCH INTERIOR
POINT METHODS: EXTENSIONS. An Arc
Search Algorithm for Convex Quadratic Programming. An Arc
Search Algorithms for QP with Box Constraints. An Arc
Search Algorithm for LCP. An Arc
Search Algorithm for Semidefinite Programming. References. Index.