Hardcover. This text provides an excellent balance of theory and application that enables you to deploy powerful algorithms, frameworks, and methodologies to solve complex optimization problems in a diverse range of industries. Each chapter is written by leading experts in the fields of parallel and distributed optimization. Collectively, the contributions serve as a complete reference to the field of combinatorial optimization, including details and findings of recent and ongoing investigations. This text provides an excellent balance of theory and application that enables you to deploy powerful algorithms, frameworks, and methodologies to solve complex optimization problems in a diverse range of industries. Each chapter is written by leading experts in the fields of parallel and distributed optimization. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

N� de r�f. du vendeur 9780471721017

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D�tails bibliographiques

Titre

Parallel Combinatorial Optimization (Hardcover)

�diteur

John Wiley & Sons Inc, Chichester

Date de parution

2006

Langue

anglais

ISBN � 10 chiffres

0471721018

ISBN � 13 chiffres

9780471721017

Reliure

Hardcover

�dition

Edition originale

�tat de l'article

new

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A propos de ce titre

Synopsis

This text provides an excellent balance of theory and application that enables you to deploy powerful algorithms, frameworks, and methodologies to solve complex optimization problems in a diverse range of industries. Each chapter is written by leading experts in the fields of parallel and distributed optimization. Collectively, the contributions serve as a complete reference to the field of combinatorial optimization, including details and findings of recent and ongoing investigations.

� propos de l?auteur

EL-GHAZALI TALBI, PHD, is Professor in the Computer Science Laboratory of the University of Lille, France. His research interests include parallel algorithms for combinatorial optimization and their applications to generic and real-world problems. Dr. Talbi leads the OPAC (Parallel Cooperative Optimization) research team; is the scientific leader of the INRIA DOLPHIN project dealing with distributed multi-objective optimization; and is active in several research and industrial projects, publications, and international conferences in the field.

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