Biologically-inspired Optimisation Methods : Parallel Algorithms, Systems and Applications

Lewis, Andrew; Mostaghim, Sanaz; Randall, Marcus

ISBN 10: 3642101771 ISBN 13: 9783642101779

Edit� par Springer, 2010

Ancien(s) ou d'occasion Couverture souple

Vendeur GreatBookPrices, Columbia, MD, Etats-Unis �valuation du vendeur 5 sur 5 �toiles

Vendeur AbeBooks depuis 6 avril 2009

Cet article sp�cifique n'est plus disponible.

Afficher tous les articles du vendeur Cr�er une demande de livres portant sur des articles similaires

Afficher tous les exemplaires de ce livre

A propos de cet article

Unread book in perfect condition. N� de r�f. du vendeur 12796485

Signaler cet article

Synopsis :

This book covers the latest theories, applications and techniques in Biologically-Inspired Optimisation Methods. Many chapters derive from studies presented at workshops and international conferences on e-Science, Grid Computing and Evolutionary computation.

Pr�sentation de l'�diteur:

Les informations fournies dans la section � A propos du livre � peuvent faire r�f�rence � une autre �dition de ce titre.

D�tails bibliographiques

Titre : Biologically-inspired Optimisation Methods :...
�diteur : Springer
Date d'�dition : 2010
Reliure : Couverture souple
Etat : As New

Meilleurs r�sultats de recherche sur AbeBooks

Image d'archives

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

Edit� par Springer, 2010

ISBN 10 : 3642101771 ISBN 13 : 9783642101779

Neuf Couverture souple

Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni

�valuation du vendeur 5 sur 5 �toiles

Etat : New. In. N� de r�f. du vendeur ria9783642101779_new

Contacter le vendeur

Acheter neuf

EUR 160,19

Exp�dition �EUR 13,84
Exp�dition depuis Royaume-Uni vers Etats-Unis

Quantit� disponible : Plus de 20 disponibles

Ajouter au panier

Image fournie par le vendeur

Biologically-Inspired Optimisation Methods

Lewis, Andrew|Mostaghim, Sanaz|Randall, Marcus

Edit� par Springer Berlin Heidelberg, 2010

ISBN 10 : 3642101771 ISBN 13 : 9783642101779

Neuf Couverture souple

Vendeur : moluna, Greven, Allemagne

�valuation du vendeur 4 sur 5 �toiles

Etat : New. N� de r�f. du vendeur 5049152

Contacter le vendeur

Acheter neuf

EUR 206,40

Exp�dition �EUR 48,99
Exp�dition depuis Allemagne vers Etats-Unis

Quantit� disponible : Plus de 20 disponibles

Ajouter au panier

Image fournie par le vendeur

Biologically-Inspired Optimisation Methods

Andrew Lewis

Edit� par Springer Berlin Heidelberg Okt 2010, 2010

ISBN 10 : 3642101771 ISBN 13 : 9783642101779

Neuf Taschenbuch

impression � la demande

Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 372 pp. Englisch. N� de r�f. du vendeur 9783642101779

Contacter le vendeur

Acheter neuf

EUR 208,64

Exp�dition �EUR 23
Exp�dition depuis Allemagne vers Etats-Unis

Quantit� disponible : 2 disponible(s)

Ajouter au panier

Image fournie par le vendeur

Autres images

Biologically-Inspired Optimisation Methods | Parallel Algorithms, Systems and Applications

Andrew Lewis (u. a.)

Edit� par Springer, 2010

ISBN 10 : 3642101771 ISBN 13 : 9783642101779

Neuf Taschenbuch

impression � la demande

Vendeur : preigu, Osnabr�ck, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Contacter le vendeur

Acheter neuf

EUR 213,95

Exp�dition �EUR 70
Exp�dition depuis Allemagne vers Etats-Unis

Quantit� disponible : 5 disponible(s)

Ajouter au panier

Image d'archives

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

Edit� par Springer, 2010

ISBN 10 : 3642101771 ISBN 13 : 9783642101779

Neuf Couverture souple

Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis

�valuation du vendeur 5 sur 5 �toiles

Etat : New. N� de r�f. du vendeur ABLIING23Mar3113020218363

Contacter le vendeur

Acheter neuf

EUR 227,01

Exp�dition �EUR 3,37
Exp�dition nationale�: Etats-Unis

Quantit� disponible : Plus de 20 disponibles

Ajouter au panier

Image fournie par le vendeur

Biologically-Inspired Optimisation Methods

Andrew Lewis

Edit� par Springer Berlin Heidelberg, Springer Berlin Heidelberg Okt 2010, 2010

ISBN 10 : 3642101771 ISBN 13 : 9783642101779

Neuf Taschenbuch

impression � la demande

Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Throughout the evolutionary history of this planet, biological systems have been able to adapt, survive and ourish despite the turmoils and upheavals of the environment. This ability has long fascinated and inspired people to emulate and adapt natural processes for application in the arti cial world of human endeavours. The realm of optimisation problems is no exception. In fact, in recent years biological systems have been the inspiration of the majority of meta-heuristic search algorithms including, but not limited to, genetic algorithms,particle swarmoptimisation, ant colony optimisation and extremal optimisation. This book presentsa continuum ofbiologicallyinspired optimisation,from the theoretical to the practical. We begin with an overview of the eld of biologically-inspired optimisation, progress to presentation of theoretical analysesandrecentextensionstoavarietyofmeta-heuristicsand nallyshow application to a number of real-worldproblems. As such, it is anticipated the book will provide a useful resource for reseachers and practitioners involved in any aspect of optimisation problems. The overviewof the eld is provided by two works co-authored by seminal thinkers in the eld. Deb�s �Evolution�s Niche in Multi-Criterion Problem Solving�, presents a very comprehensive and complete overview of almost all major issues in Evolutionary Multi-objective Optimisation (EMO). This chapter starts with the original motivation for developing EMO algorithms and provides an account of some successful problem domains on which EMO has demonstrated a clear edge over their classical counterparts.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 372 pp. Englisch. N� de r�f. du vendeur 9783642101779

Contacter le vendeur

Acheter neuf

EUR 246,09

Exp�dition �EUR 60
Exp�dition depuis Allemagne vers Etats-Unis

Quantit� disponible : 1 disponible(s)

Ajouter au panier

Image fournie par le vendeur

Biologically-Inspired Optimisation Methods : Parallel Algorithms, Systems and Applications

Andrew Lewis

Edit� par Springer Berlin Heidelberg, Springer Berlin Heidelberg, 2010

ISBN 10 : 3642101771 ISBN 13 : 9783642101779

Neuf Taschenbuch

Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. N� de r�f. du vendeur 9783642101779

Contacter le vendeur

Acheter neuf

EUR 246,09

Exp�dition �EUR 62,82
Exp�dition depuis Allemagne vers Etats-Unis

Quantit� disponible : 1 disponible(s)

Ajouter au panier

Image d'archives

Biologically-Inspired Optimisation Methods (Paperback)

Andrew Lewis

Edit� par Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin, 2010

ISBN 10 : 3642101771 ISBN 13 : 9783642101779

Neuf Paperback

Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis

�valuation du vendeur 5 sur 5 �toiles

Paperback. Etat : new. Paperback. Throughout the evolutionary history of this planet, biological systems have been able to adapt, survive and ?ourish despite the turmoils and upheavals of the environment. This ability has long fascinated and inspired people to emulate and adapt natural processes for application in the arti?cial world of human endeavours. The realm of optimisation problems is no exception. In fact, in recent years biological systems have been the inspiration of the majority of meta-heuristic search algorithms including, but not limited to, genetic algorithms,particle swarmoptimisation, ant colony optimisation and extremal optimisation. This book presentsa continuum ofbiologicallyinspired optimisation,from the theoretical to the practical. We begin with an overview of the ?eld of biologically-inspired optimisation, progress to presentation of theoretical analysesandrecentextensionstoavarietyofmeta-heuristicsand?nallyshow application to a number of real-worldproblems. As such, it is anticipated the book will provide a useful resource for reseachers and practitioners involved in any aspect of optimisation problems. The overviewof the ?eld is provided by two works co-authored by seminal thinkers in the ?eld. Deb's "Evolution's Niche in Multi-Criterion Problem Solving", presents a very comprehensive and complete overview of almost all major issues in Evolutionary Multi-objective Optimisation (EMO). This chapter starts with the original motivation for developing EMO algorithms and provides an account of some successful problem domains on which EMO has demonstrated a clear edge over their classical counterparts. This book covers the latest theories, applications and techniques in Biologically-Inspired Optimisation Methods. Many chapters derive from studies presented at workshops and international conferences on e-Science, Grid Computing and Evolutionary computation. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N� de r�f. du vendeur 9783642101779

Contacter le vendeur