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Design of Modern Heuristics Principles and Application /
Most textbooks on modern heuristics provide the reader with detailed descriptions of the functionality of single examples like genetic algorithms, genetic programming, tabu search, simulated annealing, and others, but fail to teach the underlying concepts behind these different approaches. The autho...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2011.
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| Edición: | 1st ed. 2011. |
| Colección: | Natural Computing Series,
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| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 100 | 1 | |a Rothlauf, Franz. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Design of Modern Heuristics |h [electronic resource] : |b Principles and Application / |c by Franz Rothlauf. |
| 250 | |a 1st ed. 2011. | ||
| 264 | 1 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg : |b Imprint: Springer, |c 2011. | |
| 300 | |a XI, 267 p. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
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| 490 | 1 | |a Natural Computing Series, |x 2627-6461 | |
| 505 | 0 | |a Chap. 1 -- Introduction -- Part I -- Fundamentals -- Chap. 2 -- Optimization Problems -- Chap. 3 -- Optimization Methods -- Part II -- Modern Heuristics -- Chap. 4 -- Design Elements -- Chap. 5 -- Search Strategies -- Chap. 6 -- Design Principles -- Part III Case Studies -- Chap. 7 -- High Locality Representations for Automated Programming -- Chap. 8.-Biased Modern Heuristics for the OCST Problem -- Chap. 9.-Summary -- References -- Nomenclature -- Glossary -- Index. | |
| 520 | |a Most textbooks on modern heuristics provide the reader with detailed descriptions of the functionality of single examples like genetic algorithms, genetic programming, tabu search, simulated annealing, and others, but fail to teach the underlying concepts behind these different approaches. The author takes a different approach in this textbook by focusing on the users' needs and answering three fundamental questions: First, he tells us which problems modern heuristics are expected to perform well on, and which should be left to traditional optimization methods. Second, he teaches us to systematically design the "right" modern heuristic for a particular problem by providing a coherent view on design elements and working principles. Third, he shows how we can make use of problem-specific knowledge for the design of efficient and effective modern heuristics that solve not only small toy problems but also perform well on large real-world problems. This book is written in an easy-to-read style and it is aimed at students and practitioners in computer science, operations research and information systems who want to understand modern heuristics and are interested in a guide to their systematic design and use. | ||
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 0 | |a Mathematical optimization. | |
| 650 | 0 | |a Computational intelligence. | |
| 650 | 0 | |a Business information services. | |
| 650 | 1 | 4 | |a Artificial Intelligence. |
| 650 | 2 | 4 | |a Optimization. |
| 650 | 2 | 4 | |a Computational Intelligence. |
| 650 | 2 | 4 | |a IT in Business. |
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| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9783642270703 |
| 776 | 0 | 8 | |i Printed edition: |z 9783540867982 |
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| 830 | 0 | |a Natural Computing Series, |x 2627-6461 | |
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| 950 | |a Computer Science (R0) (SpringerNature-43710) | ||