Synopsis
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.
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À propos de l?auteur
The authors are highly regarded academics and educators in theoretical computer science, and in algorithmics in particular.
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Exact Exponential Algorithms (Texts in Theoretical Computer Science. An Eatcs Series)
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Exact Exponential Algorithms (Texts in Theoretical Computer Science. An EATCS Series) [Hardcover] Fomin, Fedor V. and Kratsch, Dieter
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Fomin:Exact Exponential Algorithms (eng)
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Exact Exponential Algorithms
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Springer Berlin Heidelberg Okt 2010, 2010
ISBN 10 : 364216532X
ISBN 13 : 9783642165320
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Buch. Etat : 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. N° de réf. du vendeur 9783642165320
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Exact Exponential Algorithms
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Exact Exponential Algorithms
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Gebunden. Etat : 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. N° de réf. du vendeur 5051181
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Exact Exponential Algorithms
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ISBN 10 : 364216532X
ISBN 13 : 9783642165320
Neuf
Couverture rigide
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Buch. Etat : 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. N° de réf. du vendeur 9783642165320
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Exact Exponential Algorithms
Edité par
Springer Berlin Heidelberg, Springer Berlin Heidelberg Okt 2010, 2010
ISBN 10 : 364216532X
ISBN 13 : 9783642165320
Neuf
Couverture rigide
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Buch. Etat : Neu. 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 GmbH, Tiergartenstr. 17, 69121 Heidelberg 220 pp. Englisch. N° de réf. du vendeur 9783642165320
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