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Metaheuristics for Hard Optimization Methods and Case Studies /

Metaheuristics for Hard Optimization comprises of three parts. The first part is devoted to the detailed presentation of the four most widely known metaheuristics: • the simulated annealing method, • tabu search, • the evolutionary algorithms, • ant colony algorithms. Each one of these metaheuristic...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Dréo, Johann (Autor), Pétrowski, Alain (Autor), Siarry, Patrick (Autor), Taillard, Eric (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2006.
Edición:1st ed. 2006.
Temas:
Acceso en línea:Texto Completo

MARC

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245 1 0 |a Metaheuristics for Hard Optimization  |h [electronic resource] :  |b Methods and Case Studies /  |c by Johann Dréo, Alain Pétrowski, Patrick Siarry, Eric Taillard. 
250 |a 1st ed. 2006. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2006. 
300 |a XII, 372 p.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
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505 0 |a Presentation of the Main Metaheuristics -- Simulated Annealing -- Tabu Search -- Evolutionary Algorithms -- Ant Colony Algorithms -- Variants, Extensions and Methodological Advices -- Some Other Metaheuristics -- Extensions -- Methodology -- Case Studies -- Optimization of UMTS Radio Access Networks with Genetic Algorithms -- Genetic Algorithms Applied to Air Traffic Management -- Constraint Programming and Ant Colonies Applied to Vehicle Routing Problems. 
520 |a Metaheuristics for Hard Optimization comprises of three parts. The first part is devoted to the detailed presentation of the four most widely known metaheuristics: • the simulated annealing method, • tabu search, • the evolutionary algorithms, • ant colony algorithms. Each one of these metaheuristics is actually a family of methods, of which the essential elements are discussed. In the second part, the book presents some other less widespread metaheuristics, then, extensions of metaheuristics and some ways of research are described . The problem of the choice of a metaheuristic is posed and solution methods are discussed. The last part concentrates on three case studies from telecommunications, air traffic control, and vehicle routing. 
650 0 |a Mathematical optimization. 
650 0 |a Operations research. 
650 0 |a Artificial intelligence. 
650 0 |a Engineering mathematics. 
650 0 |a Engineering-Data processing. 
650 0 |a Industrial Management. 
650 0 |a Control engineering. 
650 0 |a Robotics. 
650 0 |a Automation. 
650 1 4 |a Optimization. 
650 2 4 |a Operations Research and Decision Theory. 
650 2 4 |a Artificial Intelligence. 
650 2 4 |a Mathematical and Computational Engineering Applications. 
650 2 4 |a Industrial Management. 
650 2 4 |a Control, Robotics, Automation. 
700 1 |a Pétrowski, Alain.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
700 1 |a Siarry, Patrick.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
700 1 |a Taillard, Eric.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
710 2 |a SpringerLink (Online service) 
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776 0 8 |i Printed edition:  |z 9783540803744 
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776 0 8 |i Printed edition:  |z 9783540230229 
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912 |a ZDB-2-SMA 
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950 |a Mathematics and Statistics (SpringerNature-11649) 
950 |a Mathematics and Statistics (R0) (SpringerNature-43713)