Parameterized algorithms [electronic resource] / Marek Cygan, Fedor V. Fomin, Łukasz Kowalik, Daniel Lokshtanov, Dániel Marx, Marcin Pilipczuk, Michał Pilipczuk, Saket Saurabh.
Cygan, Marek, 1984- author.; Fomin, Fedor V., author.; Kowalik, Łukasz, author.; Lokshtanov, Daniel, author.; Marx, Daniel, Dr., author.; Pilipczuk, Marcin, author.; Pilipczuk, Michał author.; Saurabh, Saket, author.
2015
QA276.8 .P37 2015eb
Available Online

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Title Parameterized algorithms [electronic resource] / Marek Cygan, Fedor V. Fomin, Łukasz Kowalik, Daniel Lokshtanov, Dániel Marx, Marcin Pilipczuk, Michał Pilipczuk, Saket Saurabh.
ISBN 9783319212753 electronic book
3319212753 electronic book
9783319212746
DOI https://doi.org/10.1007/978-3-319-21275-3
Published Cham : Springer, 2015.
Language English
Description 1 online resource (xvii, 613 pages) : illustrations.
Item Number 10.1007/978-3-319-21275-3 doi
Call Number QA276.8 .P37 2015eb
Dewey Decimal Classification 519.5/44
Summary 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.
Bibliography, etc. Note Includes bibliographical references and indexes.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed July 29, 2015).
Added Author Cygan, Marek, 1984- author.
Fomin, Fedor V., author.
Kowalik, Łukasz, author.
Lokshtanov, Daniel, author.
Marx, Daniel, Dr., author.
Pilipczuk, Marcin, author.
Pilipczuk, Michał author.
Saurabh, Saket, author.
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Introduction
Kernelization
Bounded Search Trees
Iterative Compression
Randomized Methods in Parameterized Algorithms
Miscellaneous
Treewidth
Finding Cuts and Separators
Advanced Kernelization Algorithms
Algebraic Techniques: Sieves, Convolutions, and Polynomials
Improving Dynamic Programming on Tree Decompositions
Matroids
Fixed-Parameter Intractability
Lower Bounds Based on the Exponential-Time Hypothesis
Lower Bounds for Kernelization.

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