Introduction to nature-inspired optimization:
"Introduction to Nature-Inspired Optimization brings together many of the innovative mathematical methods for non-linear optimization that have their origins in the way various species behave in order to optimize their chances of survival. The book describes each method, examines their strength...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
London
Academic Press
2017
|
| Ausgabe: | First edition |
| Schlagworte: | |
| Online-Zugang: | BTU01 FLA01 URL des Erstveröffentlichers |
| Zusammenfassung: | "Introduction to Nature-Inspired Optimization brings together many of the innovative mathematical methods for non-linear optimization that have their origins in the way various species behave in order to optimize their chances of survival. The book describes each method, examines their strengths and weaknesses, and where appropriate, provides the MATLAB code to give practical insight into the detailed structure of these methods and how they work. Nature-inspired algorithms emulate processes that are found in the natural world, spurring interest for optimization. Lindfield/Penny provide concise coverage to all the major algorithms, including genetic algorithms, artificial bee colony algorithms, ant colony optimization and the cuckoo search algorithm, among others. This book provides a quick reference to practicing engineers, researchers and graduate students who work in the field of optimization. Applies concepts in nature and biology to develop new algorithms for nonlinear optimizationOffers working MATLAB programs for the major algorithms described, applying them to a range of problemsProvides useful comparative studies of the algorithms, highlighting their strengths and weaknessesDiscusses the current state-of-the-field and indicates possible areas of future development."--Publisher's description |
| Beschreibung: | Includes bibliographical references and index |
| Beschreibung: | 1 online resource (xvii, 238 pages) |
| ISBN: | 9780128036662 0128036664 |
Internformat
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| 245 | 1 | 0 | |a Introduction to nature-inspired optimization |c George Lindfield, John Penny |
| 250 | |a First edition | ||
| 264 | 1 | |a London |b Academic Press |c 2017 | |
| 300 | |a 1 online resource (xvii, 238 pages) | ||
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| 500 | |a Includes bibliographical references and index | ||
| 520 | |a "Introduction to Nature-Inspired Optimization brings together many of the innovative mathematical methods for non-linear optimization that have their origins in the way various species behave in order to optimize their chances of survival. The book describes each method, examines their strengths and weaknesses, and where appropriate, provides the MATLAB code to give practical insight into the detailed structure of these methods and how they work. Nature-inspired algorithms emulate processes that are found in the natural world, spurring interest for optimization. Lindfield/Penny provide concise coverage to all the major algorithms, including genetic algorithms, artificial bee colony algorithms, ant colony optimization and the cuckoo search algorithm, among others. This book provides a quick reference to practicing engineers, researchers and graduate students who work in the field of optimization. Applies concepts in nature and biology to develop new algorithms for nonlinear optimizationOffers working MATLAB programs for the major algorithms described, applying them to a range of problemsProvides useful comparative studies of the algorithms, highlighting their strengths and weaknessesDiscusses the current state-of-the-field and indicates possible areas of future development."--Publisher's description | ||
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Datensatz im Suchindex
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| any_adam_object | |
| author | Lindfield, George |
| author_GND | (DE-588)1030295247 (DE-588)1030295050 |
| author_facet | Lindfield, George |
| author_role | aut |
| author_sort | Lindfield, George |
| author_variant | g l gl |
| building | Verbundindex |
| bvnumber | BV045131746 |
| collection | ZDB-33-ESD ZDB-33-EBS |
| ctrlnum | (ZDB-33-ESD)on1001270441 (OCoLC)1001270441 (DE-599)BVBBV045131746 |
| dewey-full | 519.6 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.6 |
| dewey-search | 519.6 |
| dewey-sort | 3519.6 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| edition | First edition |
| format | Electronic eBook |
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| id | DE-604.BV045131746 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T08:09:35Z |
| institution | BVB |
| isbn | 9780128036662 0128036664 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030521740 |
| oclc_num | 1001270441 |
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| physical | 1 online resource (xvii, 238 pages) |
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| publisher | Academic Press |
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| spelling | Lindfield, George Verfasser (DE-588)1030295247 aut Introduction to nature-inspired optimization George Lindfield, John Penny First edition London Academic Press 2017 1 online resource (xvii, 238 pages) txt rdacontent c rdamedia cr rdacarrier Includes bibliographical references and index "Introduction to Nature-Inspired Optimization brings together many of the innovative mathematical methods for non-linear optimization that have their origins in the way various species behave in order to optimize their chances of survival. The book describes each method, examines their strengths and weaknesses, and where appropriate, provides the MATLAB code to give practical insight into the detailed structure of these methods and how they work. Nature-inspired algorithms emulate processes that are found in the natural world, spurring interest for optimization. Lindfield/Penny provide concise coverage to all the major algorithms, including genetic algorithms, artificial bee colony algorithms, ant colony optimization and the cuckoo search algorithm, among others. This book provides a quick reference to practicing engineers, researchers and graduate students who work in the field of optimization. Applies concepts in nature and biology to develop new algorithms for nonlinear optimizationOffers working MATLAB programs for the major algorithms described, applying them to a range of problemsProvides useful comparative studies of the algorithms, highlighting their strengths and weaknessesDiscusses the current state-of-the-field and indicates possible areas of future development."--Publisher's description MATHEMATICS / Applied bisacsh MATHEMATICS / Probability & Statistics / General bisacsh Mathematical optimization fast Mathematical optimization MATLAB (DE-588)4329066-8 gnd rswk-swf Nichtlineare Optimierung (DE-588)4128192-5 gnd rswk-swf Nichtlineare Optimierung (DE-588)4128192-5 s MATLAB (DE-588)4329066-8 s DE-604 Penny, John Sonstige (DE-588)1030295050 oth Erscheint auch als Druck-Ausgabe 9780128036365 Erscheint auch als Druck-Ausgabe 0128036362 http://www.sciencedirect.com/science/book/9780128036365 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Lindfield, George Introduction to nature-inspired optimization MATHEMATICS / Applied bisacsh MATHEMATICS / Probability & Statistics / General bisacsh Mathematical optimization fast Mathematical optimization MATLAB (DE-588)4329066-8 gnd Nichtlineare Optimierung (DE-588)4128192-5 gnd |
| subject_GND | (DE-588)4329066-8 (DE-588)4128192-5 |
| title | Introduction to nature-inspired optimization |
| title_auth | Introduction to nature-inspired optimization |
| title_exact_search | Introduction to nature-inspired optimization |
| title_full | Introduction to nature-inspired optimization George Lindfield, John Penny |
| title_fullStr | Introduction to nature-inspired optimization George Lindfield, John Penny |
| title_full_unstemmed | Introduction to nature-inspired optimization George Lindfield, John Penny |
| title_short | Introduction to nature-inspired optimization |
| title_sort | introduction to nature inspired optimization |
| topic | MATHEMATICS / Applied bisacsh MATHEMATICS / Probability & Statistics / General bisacsh Mathematical optimization fast Mathematical optimization MATLAB (DE-588)4329066-8 gnd Nichtlineare Optimierung (DE-588)4128192-5 gnd |
| topic_facet | MATHEMATICS / Applied MATHEMATICS / Probability & Statistics / General Mathematical optimization MATLAB Nichtlineare Optimierung |
| url | http://www.sciencedirect.com/science/book/9780128036365 |
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