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  • Langue : anglais

    Edité par Springer, 2016

    3662519550 / 9783662519554

    Série : Livre 23 sur 32 - Natural Computing

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    Edité par Springer 8/23/2016, 2016

    3662519550 / 9783662519554

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    Paperback or Softback. Etat : New. Theory and Principled Methods for the Design of Metaheuristics. Book.

  • Langue : anglais

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    3662519550 / 9783662519554

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  • Langue : anglais

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    3662519550 / 9783662519554

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  • Langue : anglais

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    3662519550 / 9783662519554

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    Etat : New. pp. 290 Softcover reprint of the original 1st ed. 2014 edition NO-PA16APR2015-KAP.

  • Langue : anglais

    Edité par Springer, 2014

    3642332056 / 9783642332050

    Série : Livre 23 sur 32 - Natural Computing

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    Etat : New. pp. 292.

  • Langue : anglais

    Edité par Springer Spektrum, 2016

    3662519550 / 9783662519554

    Série : Livre 23 sur 32 - Natural Computing

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    Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.…

  • Langue : anglais

    Edité par Springer, 2014

    3642332056 / 9783642332050

    Série : Livre 23 sur 32 - Natural Computing

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    Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.…

  • Langue : anglais

    Edité par Springer, 2014

    3642332056 / 9783642332050

    Série : Livre 23 sur 32 - Natural Computing

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    Gebundene Ausgabe. Etat : Neu. 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. Sprache: Englisch Gewicht in Gramm: 554.…

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    Langue : anglais

    Edité par Springer, 2016

    3662519550 / 9783662519554

    Série : Livre 23 sur 32 - Natural Computing

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    Taschenbuch. Etat : Neu. Theory and Principled Methods for the Design of Metaheuristics | Yossi Borenstein (u. a.) | Taschenbuch | Natural Computing Series | xx | Englisch | 2016 | Springer | EAN 9783662519554 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

  • Langue : anglais

    Edité par Springer-Verlag New York Inc, 2016

    3662519550 / 9783662519554

    Série : Livre 23 sur 32 - Natural Computing

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    Paperback. Etat : Brand New. reprint edition. 292 pages. 9.30x6.20x0.69 inches. In Stock.

  • Langue : anglais

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    Etat : Sehr gut. Zustand: Sehr gut | Seiten: 292 | Sprache: Englisch | Produktart: Bücher | 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.…

  • Langue : anglais

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    3642332056 / 9783642332050

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    Hardcover. Etat : Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

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    3662519550 / 9783662519554

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  • Langue : anglais

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    3662519550 / 9783662519554

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    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.…

  • Langue : anglais

    Edité par Springer Berlin Heidelberg Jan 2014, 2014

    3642332056 / 9783642332050

    Série : Livre 23 sur 32 - Natural Computing

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    Buch. 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.…

  • Langue : anglais

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    3662519550 / 9783662519554

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    Etat : New. Print on Demand pp. 290.

  • Langue : anglais

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    Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Valuable for practitioners and researchersExplains theoretical basis of key metaheuristic techniquesContributing authors among the leading authorities on the theory of evolutionary computation, search, and heuristicsDr. Yossi .…

  • Langue : anglais

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    Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Valuable for practitioners and researchersExplains theoretical basis of key metaheuristic techniquesContributing authors among the leading authorities on the theory of evolutionary computation, search, and heuristicsDr. Yossi .…

  • Langue : anglais

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    Etat : New. PRINT ON DEMAND pp. 290.

  • Langue : anglais

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    Etat : New. PRINT ON DEMAND pp. 292.

  • Langue : anglais

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    3662519550 / 9783662519554

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    Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. 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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 292 pp. Englisch.…

  • Langue : anglais

    Edité par Springer, Springer Jan 2014, 2014

    3642332056 / 9783642332050

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    Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. 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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 292 pp. Englisch.…