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Parallel Combinatorial Optimization

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1Parallel Combinatorial Optimization

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“Parallel Combinatorial Optimization” Metadata:

  • Title: ➤  Parallel Combinatorial Optimization
  • Author:
  • Language: English
  • Number of Pages: Median: 330
  • Publisher: ➤  Wiley & Sons, Incorporated, John - Wiley-Interscience - John Wiley & Sons, Ltd. - Wiley & Sons Canada, Limited, John
  • Publish Date:
  • Publish Location: New York
  • Dewey Decimal Classification:
  • Library of Congress Classification: QA-0076.58000000.P3754 2006

“Parallel Combinatorial Optimization” Subjects and Themes:

Edition Identifiers:

Book Classifications

Access and General Info:

  • First Year Published: 2006
  • Is Full Text Available: Yes
  • Is The Book Public: No
  • Access Status: Printdisabled

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    2Solving hard combinatorial optimization problems in parallel

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    “Solving hard combinatorial optimization problems in parallel” Metadata:

    • Title: ➤  Solving hard combinatorial optimization problems in parallel
    • Author:
    • Language: English
    • Publish Date:

    Edition Identifiers:

    Access and General Info:

    • First Year Published: 1997
    • Is Full Text Available: No
    • Is The Book Public: No
    • Access Status: No_ebook

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    3Solving combinatorial optimization problems in parallel

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    “Solving combinatorial optimization problems in parallel” Metadata:

    • Title: ➤  Solving combinatorial optimization problems in parallel
    • Authors:
    • Language: English
    • Number of Pages: Median: 274
    • Publisher: Springer
    • Publish Date:
    • Publish Location: Berlin - New York
    • Dewey Decimal Classification: 519.3
    • Library of Congress Classification: QA-0402.50000000.S65 1996

    “Solving combinatorial optimization problems in parallel” Subjects and Themes:

    Edition Identifiers:

    Book Classifications

    Access and General Info:

    • First Year Published: 1996
    • Is Full Text Available: No
    • Is The Book Public: No
    • Access Status: No_ebook

    Online Access

    Downloads Are Not Available:

    The book is not public therefore the download links will not allow the download of the entire book, however, borrowing the book online is available.

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      4Solving Combinatorial Optimization Problems in Parallel

      “Solving Combinatorial Optimization Problems in Parallel” Metadata:

      • Title: ➤  Solving Combinatorial Optimization Problems in Parallel
      • Language: English
      • Publisher: Springer-Verlag
      • Publish Date:

      “Solving Combinatorial Optimization Problems in Parallel” Subjects and Themes:

      Edition Identifiers:

      Access and General Info:

      • First Year Published: 1996
      • Is Full Text Available: No
      • Is The Book Public: No
      • Access Status: No_ebook

      Online Access

      Downloads Are Not Available:

      The book is not public therefore the download links will not allow the download of the entire book, however, borrowing the book online is available.

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        Source: Harvard Library

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        1Advances in Randomized Parallel Computing

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        The technique of randomization has been employed to solve numerous prob­ lems of computing both sequentially and in parallel. Examples of randomized algorithms that are asymptotically better than their deterministic counterparts in solving various fundamental problems abound. Randomized algorithms have the advantages of simplicity and better performance both in theory and often in practice. This book is a collection of articles written by renowned experts in the area of randomized parallel computing. A brief introduction to randomized algorithms In the aflalysis of algorithms, at least three different measures of performance can be used: the best case, the worst case, and the average case. Often, the average case run time of an algorithm is much smaller than the worst case. 2 For instance, the worst case run time of Hoare's quicksort is O(n ), whereas its average case run time is only O( n log n). The average case analysis is conducted with an assumption on the input space. The assumption made to arrive at the O( n log n) average run time for quicksort is that each input permutation is equally likely. Clearly, any average case analysis is only as good as how valid the assumption made on the input space is. Randomized algorithms achieve superior performances without making any assumptions on the inputs by making coin flips within the algorithm. Any analysis done of randomized algorithms will be valid for all p0:.sible inputs.

        “Advances in Randomized Parallel Computing” Metadata:

        • Title: ➤  Advances in Randomized Parallel Computing
        • Authors:
        • Language: English
        • Publisher: Springer US,
        • Publish Date:
        • Publish Location: United States - Boston, MA
        • Genres: government publication
        • Dewey Decimal Classification: 518.1
        • Library of Congress Classification: QA76.9.A43

        “Advances in Randomized Parallel Computing” Subjects and Themes:

        Edition Specifications:

        • Number of Pages: 352p. online resource.

        Edition Identifiers:

        Book Classifications

        • Dewey Decimal (DDC): ➤  ❛518.1❜.
        • Library of Congress Classification (LCC): ➤  ❛QA76.9.A43❜.

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        2Solving combinatorial optimization problems in parallel

        methods and techniques

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        The technique of randomization has been employed to solve numerous prob­ lems of computing both sequentially and in parallel. Examples of randomized algorithms that are asymptotically better than their deterministic counterparts in solving various fundamental problems abound. Randomized algorithms have the advantages of simplicity and better performance both in theory and often in practice. This book is a collection of articles written by renowned experts in the area of randomized parallel computing. A brief introduction to randomized algorithms In the aflalysis of algorithms, at least three different measures of performance can be used: the best case, the worst case, and the average case. Often, the average case run time of an algorithm is much smaller than the worst case. 2 For instance, the worst case run time of Hoare's quicksort is O(n ), whereas its average case run time is only O( n log n). The average case analysis is conducted with an assumption on the input space. The assumption made to arrive at the O( n log n) average run time for quicksort is that each input permutation is equally likely. Clearly, any average case analysis is only as good as how valid the assumption made on the input space is. Randomized algorithms achieve superior performances without making any assumptions on the inputs by making coin flips within the algorithm. Any analysis done of randomized algorithms will be valid for all p0:.sible inputs.

        “Solving combinatorial optimization problems in parallel” Metadata:

        • Title: ➤  Solving combinatorial optimization problems in parallel
        • Authors:
        • Language: English
        • Publisher: Springer
        • Publish Date:
        • Publish Location: Germany
        • Genres: bibliography
        • Dewey Decimal Classification: 519.3
        • Library of Congress Classification: QA402.5 .S65 1996

        “Solving combinatorial optimization problems in parallel” Subjects and Themes:

        Edition Specifications:

        • Number of Pages: 274 p. : ill. ; 24 cm.

        Edition Identifiers:

        Book Classifications

        • Dewey Decimal (DDC): ➤  ❛519.3❜.
        • Library of Congress Classification (LCC): ➤  ❛QA402.5 .S65 1996❜.

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        3Solving Combinatorial Optimization Problems in Parallel Methods and Techniques

        Methods and Techniques

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        Solving combinatorial optimization problems can often lead to runtime growing exponentially as a function of the input size. But important real-world problems, industrial applications, and academic research challenges, may demand exact optimal solutions. In such situations, parallel processing can reduce the runtime from days or months, typical when one workstation is used, to a few minutes or even seconds. Partners of the CEC-sponsored SCOOP Project (Solving Combinatorial Optimization Problems in Parallel) contributed, on invitation, to this book; much attention was paid to competent coverage of the topic and the style of writing. Readers will include students, scientists, engineers, and professionals interested in the design and implementation of parallel algorithms for solving combinatorial optimization problems.

        “Solving Combinatorial Optimization Problems in Parallel Methods and Techniques” Metadata:

        • Title: ➤  Solving Combinatorial Optimization Problems in Parallel Methods and Techniques
        • Authors:
        • Language: English
        • Publisher: Springer Berlin Heidelberg :
        • Publish Date:
        • Publish Location: Germany - Berlin, Heidelberg
        • Dewey Decimal Classification: 519.3
        • Library of Congress Classification: QA76.9.A73QA76.9.S88

        “Solving Combinatorial Optimization Problems in Parallel Methods and Techniques” Subjects and Themes:

        Edition Specifications:

        • Number of Pages: ➤  1 online resource (VII, 280 p.)

        Edition Identifiers:

        Book Classifications

        • Dewey Decimal (DDC): ➤  ❛519.3❜.
        • Library of Congress Classification (LCC): ➤  ❛QA76.9.A73❜  &  ❛QA76.9.S88❜.

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