Author: Michael Jünger
Publisher: Springer
ISBN: 3540364781
Category : Mathematics
Languages : en
Pages : 219
Book Description
This book is dedicated to Jack Edmonds in appreciation of his ground breaking work that laid the foundations for a broad variety of subsequent results achieved in combinatorial optimization.The main part consists of 13 revised full papers on current topics in combinatorial optimization, presented at Aussois 2001, the Fifth Aussois Workshop on Combinatorial Optimization, March 5-9, 2001, and dedicated to Jack Edmonds.Additional highlights in this book are an account of an Aussois 2001 special session dedicated to Jack Edmonds including a speech given by William R. Pulleyblank as well as newly typeset versions of three up-to-now hardly accessible classical papers:- Submodular Functions, Matroids, and Certain Polyhedranbsp;nbsp; by Jack Edmonds- Matching: A Well-Solved Class of Integer Linear Programsnbsp;nbsp; by Jack Edmonds and Ellis L. Johnson- Theoretical Improvements in Algorithmic Efficiency for Network Flow Problemsnbsp;nbsp; by Jack Edmonds and Richard M. Karp.
Combinatorial Optimization -- Eureka, You Shrink!
Author: Michael Jünger
Publisher: Springer
ISBN: 3540364781
Category : Mathematics
Languages : en
Pages : 219
Book Description
This book is dedicated to Jack Edmonds in appreciation of his ground breaking work that laid the foundations for a broad variety of subsequent results achieved in combinatorial optimization.The main part consists of 13 revised full papers on current topics in combinatorial optimization, presented at Aussois 2001, the Fifth Aussois Workshop on Combinatorial Optimization, March 5-9, 2001, and dedicated to Jack Edmonds.Additional highlights in this book are an account of an Aussois 2001 special session dedicated to Jack Edmonds including a speech given by William R. Pulleyblank as well as newly typeset versions of three up-to-now hardly accessible classical papers:- Submodular Functions, Matroids, and Certain Polyhedranbsp;nbsp; by Jack Edmonds- Matching: A Well-Solved Class of Integer Linear Programsnbsp;nbsp; by Jack Edmonds and Ellis L. Johnson- Theoretical Improvements in Algorithmic Efficiency for Network Flow Problemsnbsp;nbsp; by Jack Edmonds and Richard M. Karp.
Publisher: Springer
ISBN: 3540364781
Category : Mathematics
Languages : en
Pages : 219
Book Description
This book is dedicated to Jack Edmonds in appreciation of his ground breaking work that laid the foundations for a broad variety of subsequent results achieved in combinatorial optimization.The main part consists of 13 revised full papers on current topics in combinatorial optimization, presented at Aussois 2001, the Fifth Aussois Workshop on Combinatorial Optimization, March 5-9, 2001, and dedicated to Jack Edmonds.Additional highlights in this book are an account of an Aussois 2001 special session dedicated to Jack Edmonds including a speech given by William R. Pulleyblank as well as newly typeset versions of three up-to-now hardly accessible classical papers:- Submodular Functions, Matroids, and Certain Polyhedranbsp;nbsp; by Jack Edmonds- Matching: A Well-Solved Class of Integer Linear Programsnbsp;nbsp; by Jack Edmonds and Ellis L. Johnson- Theoretical Improvements in Algorithmic Efficiency for Network Flow Problemsnbsp;nbsp; by Jack Edmonds and Richard M. Karp.
Exact Exponential Algorithms
Author: Fedor V. Fomin
Publisher: Springer Science & Business Media
ISBN: 3642165338
Category : Mathematics
Languages : en
Pages : 208
Book Description
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.
Publisher: Springer Science & Business Media
ISBN: 3642165338
Category : Mathematics
Languages : en
Pages : 208
Book Description
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.
Algorithmics for Hard Problems
Author: Juraj Hromkovič
Publisher: Springer
ISBN: 9783662046173
Category : Computers
Languages : en
Pages : 494
Book Description
An introduction to the methods of designing algorithms for hard computing tasks, concentrating mainly on approximate, randomized, and heuristic algorithms, and on the theoretical and experimental comparison of these approaches according to the requirements of the practice. This is the first book to systematically explain and compare all the main possibilities of attacking hard computing problems. It also closes the gap between theory and practice by providing at once a graduate textbook and a handbook for practitioners dealing with hard computing problems.
Publisher: Springer
ISBN: 9783662046173
Category : Computers
Languages : en
Pages : 494
Book Description
An introduction to the methods of designing algorithms for hard computing tasks, concentrating mainly on approximate, randomized, and heuristic algorithms, and on the theoretical and experimental comparison of these approaches according to the requirements of the practice. This is the first book to systematically explain and compare all the main possibilities of attacking hard computing problems. It also closes the gap between theory and practice by providing at once a graduate textbook and a handbook for practitioners dealing with hard computing problems.
Algorithms
Author: Sanjoy Dasgupta
Publisher: McGraw-Hill Higher Education
ISBN: 0077388496
Category : Computer algorithms
Languages : en
Pages : 338
Book Description
This text, extensively class-tested over a decade at UC Berkeley and UC San Diego, explains the fundamentals of algorithms in a story line that makes the material enjoyable and easy to digest. Emphasis is placed on understanding the crisp mathematical idea behind each algorithm, in a manner that is intuitive and rigorous without being unduly formal. Features include:The use of boxes to strengthen the narrative: pieces that provide historical context, descriptions of how the algorithms are used in practice, and excursions for the mathematically sophisticated. Carefully chosen advanced topics that can be skipped in a standard one-semester course but can be covered in an advanced algorithms course or in a more leisurely two-semester sequence.An accessible treatment of linear programming introduces students to one of the greatest achievements in algorithms. An optional chapter on the quantum algorithm for factoring provides a unique peephole into this exciting topic. In addition to the text DasGupta also offers a Solutions Manual which is available on the Online Learning Center."Algorithms is an outstanding undergraduate text equally informed by the historical roots and contemporary applications of its subject. Like a captivating novel it is a joy to read." Tim Roughgarden Stanford University
Publisher: McGraw-Hill Higher Education
ISBN: 0077388496
Category : Computer algorithms
Languages : en
Pages : 338
Book Description
This text, extensively class-tested over a decade at UC Berkeley and UC San Diego, explains the fundamentals of algorithms in a story line that makes the material enjoyable and easy to digest. Emphasis is placed on understanding the crisp mathematical idea behind each algorithm, in a manner that is intuitive and rigorous without being unduly formal. Features include:The use of boxes to strengthen the narrative: pieces that provide historical context, descriptions of how the algorithms are used in practice, and excursions for the mathematically sophisticated. Carefully chosen advanced topics that can be skipped in a standard one-semester course but can be covered in an advanced algorithms course or in a more leisurely two-semester sequence.An accessible treatment of linear programming introduces students to one of the greatest achievements in algorithms. An optional chapter on the quantum algorithm for factoring provides a unique peephole into this exciting topic. In addition to the text DasGupta also offers a Solutions Manual which is available on the Online Learning Center."Algorithms is an outstanding undergraduate text equally informed by the historical roots and contemporary applications of its subject. Like a captivating novel it is a joy to read." Tim Roughgarden Stanford University
P, NP, and NP-Completeness
Author: Oded Goldreich
Publisher: Cambridge University Press
ISBN: 1139490095
Category : Computers
Languages : en
Pages :
Book Description
The focus of this book is the P versus NP Question and the theory of NP-completeness. It also provides adequate preliminaries regarding computational problems and computational models. The P versus NP Question asks whether or not finding solutions is harder than checking the correctness of solutions. An alternative formulation asks whether or not discovering proofs is harder than verifying their correctness. It is widely believed that the answer to these equivalent formulations is positive, and this is captured by saying that P is different from NP. Although the P versus NP Question remains unresolved, the theory of NP-completeness offers evidence for the intractability of specific problems in NP by showing that they are universal for the entire class. Amazingly enough, NP-complete problems exist, and furthermore hundreds of natural computational problems arising in many different areas of mathematics and science are NP-complete.
Publisher: Cambridge University Press
ISBN: 1139490095
Category : Computers
Languages : en
Pages :
Book Description
The focus of this book is the P versus NP Question and the theory of NP-completeness. It also provides adequate preliminaries regarding computational problems and computational models. The P versus NP Question asks whether or not finding solutions is harder than checking the correctness of solutions. An alternative formulation asks whether or not discovering proofs is harder than verifying their correctness. It is widely believed that the answer to these equivalent formulations is positive, and this is captured by saying that P is different from NP. Although the P versus NP Question remains unresolved, the theory of NP-completeness offers evidence for the intractability of specific problems in NP by showing that they are universal for the entire class. Amazingly enough, NP-complete problems exist, and furthermore hundreds of natural computational problems arising in many different areas of mathematics and science are NP-complete.
The Golden Ticket
Author: Lance Fortnow
Publisher: Princeton University Press
ISBN: 0691175780
Category : Computers
Languages : en
Pages : 188
Book Description
The computer science problem whose solution could transform life as we know it The P-NP problem is the most important open problem in computer science, if not all of mathematics. Simply stated, it asks whether every problem whose solution can be quickly checked by computer can also be quickly solved by computer. The Golden Ticket provides a nontechnical introduction to P-NP, its rich history, and its algorithmic implications for everything we do with computers and beyond. Lance Fortnow traces the history and development of P-NP, giving examples from a variety of disciplines, including economics, physics, and biology. He explores problems that capture the full difficulty of the P-NP dilemma, from discovering the shortest route through all the rides at Disney World to finding large groups of friends on Facebook. The Golden Ticket explores what we truly can and cannot achieve computationally, describing the benefits and unexpected challenges of this compelling problem.
Publisher: Princeton University Press
ISBN: 0691175780
Category : Computers
Languages : en
Pages : 188
Book Description
The computer science problem whose solution could transform life as we know it The P-NP problem is the most important open problem in computer science, if not all of mathematics. Simply stated, it asks whether every problem whose solution can be quickly checked by computer can also be quickly solved by computer. The Golden Ticket provides a nontechnical introduction to P-NP, its rich history, and its algorithmic implications for everything we do with computers and beyond. Lance Fortnow traces the history and development of P-NP, giving examples from a variety of disciplines, including economics, physics, and biology. He explores problems that capture the full difficulty of the P-NP dilemma, from discovering the shortest route through all the rides at Disney World to finding large groups of friends on Facebook. The Golden Ticket explores what we truly can and cannot achieve computationally, describing the benefits and unexpected challenges of this compelling problem.
Fixed-Parameter Linear-Time Algorithms for NP-hard Graph and Hypergraph Problems Arising in Industrial Applications
Author: Bevern, René van
Publisher: Universitätsverlag der TU Berlin
ISBN: 379832705X
Category : Mathematics
Languages : en
Pages : 229
Book Description
This thesis aims for the development of efficient algorithms to exactly solve four selected NP-hard graph and hypergraph problems arising in the fields of scheduling, steel manufactoring, software engineering, radio frequency allocation, computer-aided circuit design, and social network analysis. NP-hard problems presumably cannot be solved exactly in a running time growing only polynomially with the input size. In order to still solve the considered problems efficiently, this thesis develops linear-time data reduction and fixed-parameter linear-time algorithms—algorithms that can be proven to run in linear time if certain parameters of the problem instances are constant. Besides proving linear worst-case running times, the efficiency of most of the developed algorithms is evaluated experimentally. Moreover, the limits of fixed-parameter linear-time algorithms and provably efficient and effective data reduction are shown. Diese Dissertation beschäftigt sich mit der Entwicklung effizienter Algorithmen zur exakten Lösung vier ausgewählter NP-schwerer Probleme aus der Ablaufplanung, Stahlverarbeitung, Softwaretechnik, Frequenzzuteilung, aus der computergestützten Hardwareentwicklung und der Analyse sozialer Netzwerke. NP-schwere Probleme können vermutlich nicht optimal in einer polynomiell mit der Eingabegröße wachsenden Zeit gelöst werden. Um sie dennoch effizient zu lösen, entwickelt diese Arbeit Linearzeitdatenreduktionsalgorithmen und Festparameter-Linearzeitalgorithmen – Algorithmen, die beweisbar in Linearzeit laufen, wenn bestimmte Parameter der Probleminstanzen konstant sind. Hierbei wird nicht nur bewiesen, dass die entwickelten Algorithmen in Linearzeit laufen, es findet zusätzlich eine experimentelle Evaluation der meisten der entwickelten Algorithmen statt. Ferner werden die Grenzen von Festparameter-Linearzeitalgorithmen und beweisbar effizienter und effektiver Datenreduktion aufgezeigt.
Publisher: Universitätsverlag der TU Berlin
ISBN: 379832705X
Category : Mathematics
Languages : en
Pages : 229
Book Description
This thesis aims for the development of efficient algorithms to exactly solve four selected NP-hard graph and hypergraph problems arising in the fields of scheduling, steel manufactoring, software engineering, radio frequency allocation, computer-aided circuit design, and social network analysis. NP-hard problems presumably cannot be solved exactly in a running time growing only polynomially with the input size. In order to still solve the considered problems efficiently, this thesis develops linear-time data reduction and fixed-parameter linear-time algorithms—algorithms that can be proven to run in linear time if certain parameters of the problem instances are constant. Besides proving linear worst-case running times, the efficiency of most of the developed algorithms is evaluated experimentally. Moreover, the limits of fixed-parameter linear-time algorithms and provably efficient and effective data reduction are shown. Diese Dissertation beschäftigt sich mit der Entwicklung effizienter Algorithmen zur exakten Lösung vier ausgewählter NP-schwerer Probleme aus der Ablaufplanung, Stahlverarbeitung, Softwaretechnik, Frequenzzuteilung, aus der computergestützten Hardwareentwicklung und der Analyse sozialer Netzwerke. NP-schwere Probleme können vermutlich nicht optimal in einer polynomiell mit der Eingabegröße wachsenden Zeit gelöst werden. Um sie dennoch effizient zu lösen, entwickelt diese Arbeit Linearzeitdatenreduktionsalgorithmen und Festparameter-Linearzeitalgorithmen – Algorithmen, die beweisbar in Linearzeit laufen, wenn bestimmte Parameter der Probleminstanzen konstant sind. Hierbei wird nicht nur bewiesen, dass die entwickelten Algorithmen in Linearzeit laufen, es findet zusätzlich eine experimentelle Evaluation der meisten der entwickelten Algorithmen statt. Ferner werden die Grenzen von Festparameter-Linearzeitalgorithmen und beweisbar effizienter und effektiver Datenreduktion aufgezeigt.
Exponential Time Algorithms
Author: Serge Gaspers
Publisher: Serge Gaspers
ISBN: 3639218256
Category :
Languages : en
Pages : 207
Book Description
This book studies exponential time algorithms for NP-hard problems. In this modern area, the aim is to design algorithms for combinatorially hard problems that execute provably faster than a brute-force enumeration of all candidate solutions. After an introduction and survey of the field, the text focuses first on the design and especially the analysis of branching algorithms. The analysis of these algorithms heavily relies on measures of the instances, which aim at capturing the structure of the instances, not merely their size. This makes them more appropriate to quantify the progress an algorithm makes in the process of solving a problem. Expanding the methodology to design exponential time algorithms, new techniques are then presented. Two of them combine treewidth based algorithms with branching or enumeration algorithms. Another one is the iterative compression technique, prominent in the design of parameterized algorithms, and adapted here to the design of exponential time algorithms. This book assumes basic knowledge of algorithms and should serve anyone interested in exactly solving hard problems.
Publisher: Serge Gaspers
ISBN: 3639218256
Category :
Languages : en
Pages : 207
Book Description
This book studies exponential time algorithms for NP-hard problems. In this modern area, the aim is to design algorithms for combinatorially hard problems that execute provably faster than a brute-force enumeration of all candidate solutions. After an introduction and survey of the field, the text focuses first on the design and especially the analysis of branching algorithms. The analysis of these algorithms heavily relies on measures of the instances, which aim at capturing the structure of the instances, not merely their size. This makes them more appropriate to quantify the progress an algorithm makes in the process of solving a problem. Expanding the methodology to design exponential time algorithms, new techniques are then presented. Two of them combine treewidth based algorithms with branching or enumeration algorithms. Another one is the iterative compression technique, prominent in the design of parameterized algorithms, and adapted here to the design of exponential time algorithms. This book assumes basic knowledge of algorithms and should serve anyone interested in exactly solving hard problems.
Computational Complexity
Author: Sanjeev Arora
Publisher: Cambridge University Press
ISBN: 0521424267
Category : Computers
Languages : en
Pages : 609
Book Description
New and classical results in computational complexity, including interactive proofs, PCP, derandomization, and quantum computation. Ideal for graduate students.
Publisher: Cambridge University Press
ISBN: 0521424267
Category : Computers
Languages : en
Pages : 609
Book Description
New and classical results in computational complexity, including interactive proofs, PCP, derandomization, and quantum computation. Ideal for graduate students.
Parameterized Algorithms
Author: Marek Cygan
Publisher: Springer
ISBN: 3319212753
Category : Computers
Languages : en
Pages : 618
Book Description
This comprehensive textbook presents a clean and coherent account of most fundamental tools and techniques in Parameterized Algorithms and is a self-contained guide to the area. The book covers many of the recent developments of the field, including application of important separators, branching based on linear programming, Cut & Count to obtain faster algorithms on tree decompositions, algorithms based on representative families of matroids, and use of the Strong Exponential Time Hypothesis. A number of older results are revisited and explained in a modern and didactic way. The book provides a toolbox of algorithmic techniques. Part I is an overview of basic techniques, each chapter discussing a certain algorithmic paradigm. The material covered in this part can be used for an introductory course on fixed-parameter tractability. Part II discusses more advanced and specialized algorithmic ideas, bringing the reader to the cutting edge of current research. Part III presents complexity results and lower bounds, giving negative evidence by way of W[1]-hardness, the Exponential Time Hypothesis, and kernelization lower bounds. All the results and concepts are introduced at a level accessible to graduate students and advanced undergraduate students. Every chapter is accompanied by exercises, many with hints, while the bibliographic notes point to original publications and related work.
Publisher: Springer
ISBN: 3319212753
Category : Computers
Languages : en
Pages : 618
Book Description
This comprehensive textbook presents a clean and coherent account of most fundamental tools and techniques in Parameterized Algorithms and is a self-contained guide to the area. The book covers many of the recent developments of the field, including application of important separators, branching based on linear programming, Cut & Count to obtain faster algorithms on tree decompositions, algorithms based on representative families of matroids, and use of the Strong Exponential Time Hypothesis. A number of older results are revisited and explained in a modern and didactic way. The book provides a toolbox of algorithmic techniques. Part I is an overview of basic techniques, each chapter discussing a certain algorithmic paradigm. The material covered in this part can be used for an introductory course on fixed-parameter tractability. Part II discusses more advanced and specialized algorithmic ideas, bringing the reader to the cutting edge of current research. Part III presents complexity results and lower bounds, giving negative evidence by way of W[1]-hardness, the Exponential Time Hypothesis, and kernelization lower bounds. All the results and concepts are introduced at a level accessible to graduate students and advanced undergraduate students. Every chapter is accompanied by exercises, many with hints, while the bibliographic notes point to original publications and related work.