Exact Exponential Algorithms by Fomin Fedor (11 results)
Language: English
Published by Springer, 2010
Series: Book 32 of 45 - Texts in Theoretical Computer Science. An EATCS
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hardcover. Condition: 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.
Language: English
Published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin, 2012
Series: Book 32 of 45 - Texts in Theoretical Computer Science. An EATCS
- Softcover
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Paperback. Condition: new. Paperback. 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 o…f 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Language: English
Published by Springer, 2010
Series: Book 32 of 45 - Texts in Theoretical Computer Science. An EATCS
- Hardcover
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Condition: 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.
Language: English
Published by Springer, 2013
Series: Book 32 of 45 - Texts in Theoretical Computer Science. An EATCS
- Softcover
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Paperback. Condition: Brand New. 2010 edition. 220 pages. 9.21x6.14x0.46 inches. In Stock.
Language: English
Published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin, 2012
Series: Book 32 of 45 - Texts in Theoretical Computer Science. An EATCS
- Softcover
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Paperback. Condition: new. Paperback. 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 o…f 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. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Language: English
Published by Springer, 2012
Series: Book 32 of 45 - Texts in Theoretical Computer Science. An EATCS
- Softcover
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Taschenbuch. Condition: Neu. Exact Exponential Algorithms | Fedor V. Fomin (u. a.) | Taschenbuch | Texts in Theoretical Computer Science. An EATCS Series | xiv | Englisch | 2012 | Springer | EAN 9783642265662 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]s…pringer[dot]com | Anbieter: preigu.
Language: English
Published by Springer, Springer Vieweg, 2010
Series: Book 32 of 45 - Texts in Theoretical Computer Science. An EATCS
- Hardcover
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Buch. Condition: 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 bound…ed 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.
Language: English
Published by Springer Berlin Heidelberg, 2012
Series: Book 32 of 45 - Texts in Theoretical Computer Science. An EATCS
- Softcover
- Print on Demand
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Condition: 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 re…searchersTh.
Language: English
Published by Springer, Springer Gabler Dez 2012, 2012
Series: Book 32 of 45 - Texts in Theoretical Computer Science. An EATCS
- Softcover
- Print on Demand
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Taschenbuch. Condition: 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.
Language: English
Published by Springer Berlin Heidelberg, 2010
Series: Book 32 of 45 - Texts in Theoretical Computer Science. An EATCS
- Hardcover
- Print on Demand
Seller: moluna, Greven, Germanymoluna
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Gebunden. Condition: 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 introduct…ion for researchersTh.
Language: English
Published by Springer, Springer Vieweg Okt 2010, 2010
Series: Book 32 of 45 - Texts in Theoretical Computer Science. An EATCS
- Hardcover
- Print on Demand
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
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Buch. Condition: 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 prob…lem 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.
