Biologically-Inspired Optimisation Methods: Parallel Algorithms, Systems and Applications: 210 (Studies in Computational Intelligence, 210) - Tapa dura

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9783642012617: Biologically-Inspired Optimisation Methods: Parallel Algorithms, Systems and Applications: 210 (Studies in Computational Intelligence, 210)
Tapa dura
ISBN 10: 3642012612 ISBN 13: 9783642012617
Editorial: Springer, 2009

Sinopsis

Evolution’s Niche in Multi-Criterion Problem Solving.- Applications of Parallel Platforms and Models in Evolutionary Multi-Objective Optimization.- Asynchronous Multi-Objective Optimisation in Unreliable Distributed Environments.- Dynamic Problems and Nature Inspired Meta-heuristics.- Relaxation Labelling Using Distributed Neural Networks.- Extremal Optimisation for Assignment Type Problems.- Niching for Ant Colony Optimisation.- Using Ant Colony Optimisation to Construct Meander-Line RFID Antennas.- The Radio Network Design Optimization Problem.- Strategies for Decentralised Balancing Power.- An Analysis of Dynamic Mutation Operators for Conformational Sampling.- Evolving Computer Chinese Chess Using Guided Learning.

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De la contraportada

Humanity has often turned to Nature for inspiration to help it solve its problems.  The systems She provides are often based on simple rules and premises, yet are able to adapt to new and complex environments quickly and efficiently.  Problems from a range of human endeavours, including, science, engineering and economics, require us to find good quality solutions in exponentially large search spaces, a task that often requires vast amounts computational resources and effort.  In this book, the contributing authors solve these problems by modelling aspects of the natural world, from the flocking of birds and fish, the operation of colonies of ants through to chromosome reproduction and beyond.  Many of the contributions represent extended studies of work presented at a number of workshops on Biologically-Inspired Optimisation Methods at international conferences on e-Science, Grid Computing, and Evolutionary Computation.  A variety of chapters from some of the leading experts in the field present an overview of the state-of-the-art, recent advances in theoretical and practical ideas and techniques, and details of application of these methods to a range of benchmark and real world problems.

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Editorial
Springer
Año de publicación
2009
Idioma
Inglés
ISBN 10 
3642012612
ISBN 13 
9783642012617
Encuadernación
Tapa dura
Número de páginas
376
Contacto del fabricante
Springer-Verlag GmbH
customerservice@springernature.com

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Alemania

Otras ediciones populares con el mismo título

9783642101779: Biologically-Inspired Optimisation Methods: Parallel Algorithms, Systems and Applications: 210 (Studies in Computational Intelligence)

Edición Destacada

ISBN 10:  3642101771 ISBN 13:  9783642101779
Editorial: Springer, 2010
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