Metaheuristics, and evolutionary algorithms in particular, are known to provide efficient, adaptable solutions for many real-world problems, but the often informal way in which they are defined and applied has led to misconceptions, and even successful applications are sometimes the outcome of trial and error. Ideally, theoretical studies should explain when and why metaheuristics work, but the challenge is huge: mathematical analysis requires significant effort even for simple scenarios and real-life problems are usually quite complex.
In this book the editors establish a bridge between theory and practice, presenting principled methods that incorporate problem knowledge in evolutionary algorithms and other metaheuristics. The book consists of 11 chapters dealing with the following topics: theoretical results that show what is not possible, an assessment of unsuccessful lines of empirical research; methods for rigorously defining the appropriate scope of problems while acknowledging the compromise between the class of problems to which a search algorithm is applied and its overall expected performance; the top-down principled design of search algorithms, in particular showing that it is possible to design algorithms that are provably good for some rigorously defined classes; and, finally, principled practice, that is reasoned and systematic approaches to setting up experiments, metaheuristic adaptation to specific problems, and setting parameters.
With contributions by some of the leading researchers in this domain, this book will be of significant value to scientists, practitioners, and graduate students in the areas of evolutionary computing, metaheuristics, and computational intelligence.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Dr. Yossi Borenstein is the head of risk analytics at the company VisualDNA; he previously held a position at the University of Hertfordshire, and he received his PhD from the University of Essex; his research interests include data analysis, information retrieval, stochastic optimization, artificial intelligence, and evolutionary computation.
Dr. Alberto Moraglio is a lecturer in the Dept. of Computer Science of the University of Exeter. He previously held positions at the University of Birmingham and the University of Coimbra, and he received his PhD from the University of Essex. His research focus is the theory of evolutionary computation.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : New. N° de réf. du vendeur 27175146-n
Quantité disponible : Plus de 20 disponibles
Vendeur : BargainBookStores, Grand Rapids, MI, Etats-Unis
Paperback or Softback. Etat : New. Theory and Principled Methods for the Design of Metaheuristics. Book. N° de réf. du vendeur BBS-9783662519554
Quantité disponible : 5 disponible(s)
Vendeur : California Books, Miami, FL, Etats-Unis
Etat : New. N° de réf. du vendeur I-9783662519554
Quantité disponible : Plus de 20 disponibles
Vendeur : Chiron Media, Wallingford, Royaume-Uni
Paperback. Etat : New. N° de réf. du vendeur 6666-IUK-9783662519554
Quantité disponible : 10 disponible(s)
Vendeur : Brook Bookstore On Demand, Napoli, NA, Italie
Etat : new. Questo è un articolo print on demand. N° de réf. du vendeur 552375ed828acdaea18c1cf554d000ca
Quantité disponible : Plus de 20 disponibles
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Metaheuristics, and evolutionary algorithms in particular, are known to provide efficient, adaptable solutions for many real-world problems, but the often informal way in which they are defined and applied has led to misconceptions, and even successful applications are sometimes the outcome of trial and error. Ideally, theoretical studies should explain when and why metaheuristics work, but the challenge is huge: mathematical analysis requires significant effort even for simple scenarios and real-life problems are usually quite complex. In this book the editors establish a bridge between theory and practice, presenting principled methods that incorporate problem knowledge in evolutionary algorithms and other metaheuristics. The book consists of 11 chapters dealing with the following topics: theoretical results that show what is not possible, an assessment of unsuccessful lines of empirical research; methods for rigorously defining the appropriate scope of problems while acknowledging the compromise between the class of problems to which a search algorithm is applied and its overall expected performance; the top-down principled design of search algorithms, in particular showing that it is possible to design algorithms that are provably good for some rigorously defined classes; and, finally, principled practice, that is reasoned and systematic approaches to setting up experiments, metaheuristic adaptation to specific problems, and setting parameters. With contributions by some of the leading researchers in this domain, this book will be of significant value to scientists, practitioners, and graduate students in the areas of evolutionary computing, metaheuristics, and computational intelligence. 292 pp. Englisch. N° de réf. du vendeur 9783662519554
Quantité disponible : 2 disponible(s)
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Etat : New. N° de réf. du vendeur 27175146-n
Quantité disponible : Plus de 20 disponibles
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Etat : New. In English. N° de réf. du vendeur ria9783662519554_new
Quantité disponible : Plus de 20 disponibles
Vendeur : Books Puddle, Woodside, NY, Etats-Unis
Etat : New. pp. 290 Softcover reprint of the original 1st ed. 2014 edition NO-PA16APR2015-KAP. N° de réf. du vendeur 26378097201
Quantité disponible : 4 disponible(s)
Vendeur : Majestic Books, Hounslow, Royaume-Uni
Etat : New. Print on Demand pp. 290. N° de réf. du vendeur 385806830
Quantité disponible : 4 disponible(s)