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Sequential Approximate Multiobjective Optimization Using Computational Intelligence
This book highlights a new direction of multiobjective optimzation, which has never been treated in previous publications. When the function form of objective functions is not known explicitly as encountered in many practical problems, sequential approximate optimization based on metamodels is an ef...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , , |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2009.
|
| Edición: | 1st ed. 2009. |
| Colección: | Vector Optimization,
|
| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
| LEADER | 00000nam a22000005i 4500 | ||
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| 001 | 978-3-540-88910-6 | ||
| 003 | DE-He213 | ||
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| 008 | 100301s2009 gw | s |||| 0|eng d | ||
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| 024 | 7 | |a 10.1007/978-3-540-88910-6 |2 doi | |
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| 100 | 1 | |a Nakayama, Hirotaka. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Sequential Approximate Multiobjective Optimization Using Computational Intelligence |h [electronic resource] / |c by Hirotaka Nakayama, Yeboon Yun, Min Yoon. |
| 250 | |a 1st ed. 2009. | ||
| 264 | 1 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg : |b Imprint: Springer, |c 2009. | |
| 300 | |a XVI, 200 p. 111 illus. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
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| 490 | 1 | |a Vector Optimization, |x 1867-898X | |
| 505 | 0 | |a Basic Concepts of Multi-objective Optimization -- Interactive Programming Methods for Multi-objective Optimization -- Generation of Pareto Frontier by Genetic Algorithms -- Multi-objective Optimization and Computational Intelligence -- Sequential Approximate Optimization -- Combining Aspiration Level Approach and SAMO -- Engineering Applications. | |
| 520 | |a This book highlights a new direction of multiobjective optimzation, which has never been treated in previous publications. When the function form of objective functions is not known explicitly as encountered in many practical problems, sequential approximate optimization based on metamodels is an effective tool from a practical viewpoint. Several sophisticated methods for sequential approximate multiobjective optimization using computational intelligence are introduced along with real applications, mainly engineering problems, in this book. | ||
| 650 | 0 | |a Mathematical models. | |
| 650 | 0 | |a Operations research. | |
| 650 | 0 | |a Management science. | |
| 650 | 0 | |a Computer science. | |
| 650 | 0 | |a Mathematical optimization. | |
| 650 | 0 | |a Computer science-Mathematics. | |
| 650 | 0 | |a Discrete mathematics. | |
| 650 | 1 | 4 | |a Mathematical Modeling and Industrial Mathematics. |
| 650 | 2 | 4 | |a Operations Research, Management Science . |
| 650 | 2 | 4 | |a Theory of Computation. |
| 650 | 2 | 4 | |a Operations Research and Decision Theory. |
| 650 | 2 | 4 | |a Optimization. |
| 650 | 2 | 4 | |a Discrete Mathematics in Computer Science. |
| 700 | 1 | |a Yun, Yeboon. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 700 | 1 | |a Yoon, Min. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9783642100307 |
| 776 | 0 | 8 | |i Printed edition: |z 9783540891239 |
| 776 | 0 | 8 | |i Printed edition: |z 9783540889090 |
| 830 | 0 | |a Vector Optimization, |x 1867-898X | |
| 856 | 4 | 0 | |u https://doi.uam.elogim.com/10.1007/978-3-540-88910-6 |z Texto Completo |
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| 950 | |a Mathematics and Statistics (SpringerNature-11649) | ||
| 950 | |a Mathematics and Statistics (R0) (SpringerNature-43713) | ||