Mathematical Theory of Optimization:
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Boston, MA
Springer US
2001
|
| Schriftenreihe: | Nonconvex Optimization and Its Applications
56 |
| Schlagwörter: | |
| Links: | https://doi.org/10.1007/978-1-4757-5795-8 |
| Beschreibung: | Optimization is of central importance in all sciences. Nature inherently seeks optimal solutions. For example, light travels through the "shortest" path and the folded state of a protein corresponds to the structure with the "minimum" potential energy. In combinatorial optimization, there are numerous computationally hard problems arising in real world applications, such as floorplanning in VLSI designs and Steiner trees in communication networks. For these problems, the exact optimal solution is not currently real-time computable. One usually computes an approximate solution with various kinds of heuristics. Recently, many approaches have been developed that link the discrete space of combinatorial optimization to the continuous space of nonlinear optimization through geometric, analytic, and algebraic techniques. Many researchers have found that such approaches lead to very fast and efficient heuristics for solving large problems. Although almost all such heuristics work well in practice there is no solid theoretical analysis, except Karmakar's algorithm for linear programming. With this situation in mind, we decided to teach a seminar on nonlinear optimization with emphasis on its mathematical foundations. This book is the result of that seminar. During the last decades many textbooks and monographs in nonlinear optimization have been published. Why should we write this new one? What is the difference of this book from the others? The motivation for writing this book originated from our efforts to select a textbook for a graduate seminar with focus on the mathematical foundations of optimization |
| Umfang: | 1 Online-Ressource (XIII, 273 p) |
| ISBN: | 9781475757958 9781441952028 |
| ISSN: | 1571-568X |
| DOI: | 10.1007/978-1-4757-5795-8 |
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| 500 | |a Optimization is of central importance in all sciences. Nature inherently seeks optimal solutions. For example, light travels through the "shortest" path and the folded state of a protein corresponds to the structure with the "minimum" potential energy. In combinatorial optimization, there are numerous computationally hard problems arising in real world applications, such as floorplanning in VLSI designs and Steiner trees in communication networks. For these problems, the exact optimal solution is not currently real-time computable. One usually computes an approximate solution with various kinds of heuristics. Recently, many approaches have been developed that link the discrete space of combinatorial optimization to the continuous space of nonlinear optimization through geometric, analytic, and algebraic techniques. Many researchers have found that such approaches lead to very fast and efficient heuristics for solving large problems. Although almost all such heuristics work well in practice there is no solid theoretical analysis, except Karmakar's algorithm for linear programming. With this situation in mind, we decided to teach a seminar on nonlinear optimization with emphasis on its mathematical foundations. This book is the result of that seminar. During the last decades many textbooks and monographs in nonlinear optimization have been published. Why should we write this new one? What is the difference of this book from the others? The motivation for writing this book originated from our efforts to select a textbook for a graduate seminar with focus on the mathematical foundations of optimization | ||
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| discipline | Mathematik |
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| id | DE-604.BV042421674 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-20T17:10:45Z |
| institution | BVB |
| isbn | 9781475757958 9781441952028 |
| issn | 1571-568X |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-027857091 |
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| physical | 1 Online-Ressource (XIII, 273 p) |
| psigel | ZDB-2-SMA ZDB-2-BAE ZDB-2-SMA_Archive |
| publishDate | 2001 |
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| publisher | Springer US |
| record_format | marc |
| series2 | Nonconvex Optimization and Its Applications |
| spellingShingle | Du, Ding-Zhu Mathematical Theory of Optimization Mathematics Information theory Computer science Computer science / Mathematics Algorithms Mathematical optimization Optimization Theory of Computation Computational Mathematics and Numerical Analysis Mathematics of Computing Informatik Mathematik Optimierung (DE-588)4043664-0 gnd |
| subject_GND | (DE-588)4043664-0 |
| title | Mathematical Theory of Optimization |
| title_auth | Mathematical Theory of Optimization |
| title_exact_search | Mathematical Theory of Optimization |
| title_full | Mathematical Theory of Optimization edited by Ding-Zhu Du, Panos M. Pardalos, Weili Wu |
| title_fullStr | Mathematical Theory of Optimization edited by Ding-Zhu Du, Panos M. Pardalos, Weili Wu |
| title_full_unstemmed | Mathematical Theory of Optimization edited by Ding-Zhu Du, Panos M. Pardalos, Weili Wu |
| title_short | Mathematical Theory of Optimization |
| title_sort | mathematical theory of optimization |
| topic | Mathematics Information theory Computer science Computer science / Mathematics Algorithms Mathematical optimization Optimization Theory of Computation Computational Mathematics and Numerical Analysis Mathematics of Computing Informatik Mathematik Optimierung (DE-588)4043664-0 gnd |
| topic_facet | Mathematics Information theory Computer science Computer science / Mathematics Algorithms Mathematical optimization Optimization Theory of Computation Computational Mathematics and Numerical Analysis Mathematics of Computing Informatik Mathematik Optimierung |
| url | https://doi.org/10.1007/978-1-4757-5795-8 |
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