Isbn: 9783642025372 - experimental methods for the analysis of optimization algorithms (11 risultati)

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    • Lingua: Inglese

      Editore: Springer, 2010

      3642025374 / 9783642025372

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    • Lingua: Inglese

      Editore: Springer, 2010

      3642025374 / 9783642025372

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    • Lingua: Inglese

      Editore: Springer, 2010

      3642025374 / 9783642025372

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      Condizione: New. pp. 480.

    • Lingua: Inglese

      Editore: Springer-Verlag New York Inc, 2010

      3642025374 / 9783642025372

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      Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books

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      Hardcover. Condizione: Brand New. 457 pages. 9.25x6.25x0.75 inches. In Stock.

    • Lingua: Inglese

      Editore: Springer, 2010

      3642025374 / 9783642025372

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      Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand

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    • Lingua: Inglese

      Editore: Springer Berlin Heidelberg Nov 2010, 2010

      3642025374 / 9783642025372

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      Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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      Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In operations research and computer science it is common practice to evaluate the performance of optimization algorithms on the basis of computational results, and the experimental approach should follow accepted principles that guarantee the reliability and reproducibility of results. However, computational experiments differ from those in other sciences, and the last decade has seen considerable methodological research devoted to understanding the particular features of such experiments and assessing the related statistical methods. This book consists of methodological contributions on different scenarios of experimental analysis. The first part overviews the main issues in the experimental analysis of algorithms, and discusses the experimental cycle of algorithm development; the second part treats the characterization by means of statistical distributions of algorithm performance in terms of solution quality, runtime and other measures; and the third part collects advanced methods from experimental design for configuring and tuning algorithms on a specific class of instances with the goal of using the least amount of experimentation. The contributor list includes leading scientists in algorithm design, statistical design, optimization and heuristics, and most chapters provide theoretical background and are enriched with case studies. This book is written for researchers and practitioners in operations research and computer science who wish to improve the experimental assessment of optimization algorithms and, consequently, their design. 480 pp. Englisch.

    • Lingua: Inglese

      Editore: Springer Berlin Heidelberg, 2010

      3642025374 / 9783642025372

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      Da: moluna, Greven, Germaniamoluna

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      Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. First book to offer full treatment on this subjectContributor include leading scientists in algorithm design, statistical design, optimization and heuristicsMost chapters provide theoretical background and are enriched with case studies.

    • Lingua: Inglese

      Editore: Springer, Springer Vieweg Nov 2010, 2010

      3642025374 / 9783642025372

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      Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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      Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In operations research and computer science it is common practice to evaluate the performance of optimization algorithms on the basis of computational results, and the experimental approach should follow accepted principles that guarantee the reliability and reproducibility of results. However, computational experiments differ from those in other sciences, and the last decade has seen considerable methodological research devoted to understanding the particular features of such experiments and assessing the related statistical methods.This book consists of methodological contributions on different scenarios of experimental analysis. The first part overviews the main issues in the experimental analysis of algorithms, and discusses the experimental cycle of algorithm development; the second part treats the characterization by means of statistical distributions of algorithm performance in terms of solution quality, runtime and other measures; and the third part collects advanced methods from experimental design for configuring and tuning algorithms on a specific class of instances with the goal of using the least amount of experimentation. The contributor list includes leading scientists in algorithm design, statistical design, optimization and heuristics, and most chapters provide theoretical background and are enriched with case studies.This book is written for researchers and practitioners in operations research and computer science who wish to improve the experimental assessment of optimization algorithms and, consequently, their design.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 480 pp. Englisch.

    • Lingua: Inglese

      Editore: Springer, 2010

      3642025374 / 9783642025372

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      Da: Majestic Books, Hounslow, Regno UnitoMajestic Books

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      Condizione: New. Print on Demand pp. 480 93 Illus.

    • Lingua: Inglese

      Editore: Springer, 2010

      3642025374 / 9783642025372

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      Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios

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      Condizione: New. PRINT ON DEMAND pp. 480.

    • Lingua: Inglese

      Editore: J.B. Metzler, 2010

      3642025374 / 9783642025372

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      Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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      EUR 212,09

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      Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In operations research and computer science it is common practice to evaluate the performance of optimization algorithms on the basis of computational results, and the experimental approach should follow accepted principles that guarantee the reliability and reproducibility of results. However, computational experiments differ from those in other sciences, and the last decade has seen considerable methodological research devoted to understanding the particular features of such experiments and assessing the related statistical methods. This book consists of methodological contributions on different scenarios of experimental analysis. The first part overviews the main issues in the experimental analysis of algorithms, and discusses the experimental cycle of algorithm development; the second part treats the characterization by means of statistical distributions of algorithm performance in terms of solution quality, runtime and other measures; and the third part collects advanced methods from experimental design for configuring and tuning algorithms on a specific class of instances with the goal of using the least amount of experimentation. The contributor list includes leading scientists in algorithm design, statistical design, optimization and heuristics, and most chapters provide theoretical background and are enriched with case studies. This book is written for researchers and practitioners in operations research and computer science who wish to improve the experimental assessment of optimization algorithms and, consequently, their design.