Isbn: 9783642165320 - exact exponential algorithms (8 risultati)

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  • Lingua: Inglese

    Editore: Springer, 2010

    364216532X / 9783642165320

    Serie: Libro 32 di 45 - Texts in Theoretical Computer Science. An EATCS

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    hardcover. Condizione: Like New. Most items will be dispatched the same or the next working day. An apparently unread copy in perfect condition. Dust cover is intact with no nicks or tears. Spine has no signs of creasing. Pages are clean and not marred by notes or folds of any kind.

  • Lingua: Inglese

    Editore: Springer, 2010

    364216532X / 9783642165320

    Serie: Libro 32 di 45 - Texts in Theoretical Computer Science. An EATCS

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    Condizione: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,550grams, ISBN:9783642165320.

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  • Lingua: Inglese

    Editore: Springer Spektrum, 2010

    364216532X / 9783642165320

    Serie: Libro 32 di 45 - Texts in Theoretical Computer Science. An EATCS

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

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    Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - For a long time computer scientists have distinguished between fast and slow algo rithms. Fast (or good) algorithms are the algorithms that run in polynomial time, which means that the number of steps required for the algorithm to solve a problem is bounded by some polynomial in the length of the input. All other algorithms are slow (or bad). The running time of slow algorithms is usually exponential. This book is about bad algorithms. There are several reasons why we are interested in exponential time algorithms. Most of us believe that there are many natural problems which cannot be solved by polynomial time algorithms. The most famous and oldest family of hard problems is the family of NP complete problems. Most likely there are no polynomial time al gorithms solving these hard problems and in the worst case scenario the exponential running time is unavoidable. Every combinatorial problem is solvable in nite time by enumerating all possi ble solutions, i. e. by brute force search. But is brute force search always unavoid able De nitely not. Already in the nineteen sixties and seventies it was known that some NP complete problems can be solved signi cantly faster than by brute force search. Three classic examples are the following algorithms for the TRAVELLING SALESMAN problem, MAXIMUM INDEPENDENT SET, and COLORING.

  • Lingua: Inglese

    Editore: Springer, 2010

    364216532X / 9783642165320

    Serie: Libro 32 di 45 - Texts in Theoretical Computer Science. An EATCS

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  • Lingua: Inglese

    Editore: Springer Berlin Heidelberg Okt 2010, 2010

    364216532X / 9783642165320

    Serie: Libro 32 di 45 - Texts in Theoretical Computer Science. An EATCS

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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 -For a long time computer scientists have distinguished between fast and slow algo rithms. Fast (or good) algorithms are the algorithms that run in polynomial time, which means that the number of steps required for the algorithm to solve a problem is bounded by some polynomial in the length of the input. All other algorithms are slow (or bad). The running time of slow algorithms is usually exponential. This book is about bad algorithms. There are several reasons why we are interested in exponential time algorithms. Most of us believe that there are many natural problems which cannot be solved by polynomial time algorithms. The most famous and oldest family of hard problems is the family of NP complete problems. Most likely there are no polynomial time al gorithms solving these hard problems and in the worst case scenario the exponential running time is unavoidable. Every combinatorial problem is solvable in nite time by enumerating all possi ble solutions, i. e. by brute force search. But is brute force search always unavoid able De nitely not. Already in the nineteen sixties and seventies it was known that some NP complete problems can be solved signi cantly faster than by brute force search. Three classic examples are the following algorithms for the TRAVELLING SALESMAN problem, MAXIMUM INDEPENDENT SET, and COLORING. 220 pp. Englisch.

  • Lingua: Inglese

    Editore: Springer Berlin Heidelberg, 2010

    364216532X / 9783642165320

    Serie: Libro 32 di 45 - Texts in Theoretical Computer Science. An EATCS

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    Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Textbook has been class-tested by the authors and their collaboratorsText is supported throughout with exercises and notes for further readingComprehensive introduction for researchersComprehensive introduction for researchersTh.

  • Lingua: Inglese

    Editore: Springer, Springer Vieweg Okt 2010, 2010

    364216532X / 9783642165320

    Serie: Libro 32 di 45 - Texts in Theoretical Computer Science. An EATCS

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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 -For a long time computer scientists have distinguished between fast and slow algo rithms. Fast (or good) algorithms are the algorithms that run in polynomial time, which means that the number of steps required for the algorithm to solve a problem is bounded by some polynomial in the length of the input. All other algorithms are slow (or bad). The running time of slow algorithms is usually exponential. This book is about bad algorithms. There are several reasons why we are interested in exponential time algorithms. Most of us believe that there are many natural problems which cannot be solved by polynomial time algorithms. The most famous and oldest family of hard problems is the family of NP complete problems. Most likely there are no polynomial time al gorithms solving these hard problems and in the worst case scenario the exponential running time is unavoidable. Every combinatorial problem is solvable in nite time by enumerating all possi ble solutions, i. e. by brute force search. But is brute force search always unavoid able De nitely not. Already in the nineteen sixties and seventies it was known that some NP complete problems can be solved signi cantly faster than by brute force search. Three classic examples are the following algorithms for the TRAVELLING SALESMAN problem, MAXIMUM INDEPENDENT SET, and COLORING.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 220 pp. Englisch.