High Performance Optimization / edited by Hans Frenk, Kees Roos, Tamás Terlaky, Shuzhong Zhang
(Applied Optimization ; 33)
| データ種別 | 電子ブック |
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| 出版情報 | Boston, MA : Springer US : Imprint: Springer , 2000 |
| 本文言語 | 英語 |
| 大きさ | XXII, 474 p : online resource |
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| 内容注記 | 1 Introduction 2 Duality 3 Polynomiality of Path-following Methods 4 Self-Dual Embedding Technique 5 Properties of the Central Path 6 Superlinear Convergence 7 Central Region Method 8 An Implementation of the Homogeneous Algorithm 9 A Simplified Correctness Proof for Interior Point Algorithm 10 New Analysis of Newton Methods for LCP 11 Numerical Evaluation of SDPA 12 Robust Modeling of Multi-Stage Portfolio Problems 13 An Interior Point SQP Parallel B&B Method 14 Solving Linear Ordering Problems 15 Finite Element Methods for Solving Parabolic Inverse Problems 16 Error Bounds For Quadratic Systems 17 Squared Functional Systems and Optimization Problems 18 Interior Point Methods: Current Status and Future Directions |
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| 一般注記 | For a long time the techniques of solving linear optimization (LP) problems improved only marginally. Fifteen years ago, however, a revolutionary discovery changed everything. A new `golden age' for optimization started, which is continuing up to the current time. What is the cause of the excitement? Techniques of linear programming formed previously an isolated body of knowledge. Then suddenly a tunnel was built linking it with a rich and promising land, part of which was already cultivated, part of which was completely unexplored. These revolutionary new techniques are now applied to solve conic linear problems. This makes it possible to model and solve large classes of essentially nonlinear optimization problems as efficiently as LP problems. This volume gives an overview of the latest developments of such `High Performance Optimization Techniques'. The first part is a thorough treatment of interior point methods for semidefinite programming problems. The second part reviews today's most exciting research topics and results in the area of convex optimization. Audience: This volume is for graduate students and researchers who are interested in modern optimization techniques |
| 著者標目 | Frenk, Hans editor Roos, Kees editor Terlaky, Tamás editor Zhang, Shuzhong editor SpringerLink (Online service) |
| 件 名 | LCSH:Mathematics LCSH:System theory LCSH:Number theory LCSH:Mathematical optimization LCSH:Calculus of variations FREE:Mathematics FREE:Optimization FREE:Mathematics, general FREE:Calculus of Variations and Optimal Control; Optimization FREE:Systems Theory, Control FREE:Number Theory |
| 分 類 | DC23:519.6 |
| 巻冊次 | ISBN:9781475732160 
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| ISBN | 9781475732160 |
| URL | http://dx.doi.org/10.1007/978-1-4757-3216-0 |
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