Exponential Time Algorithms
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Exponential Time Algorithms
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.
Computer Science Illuminated
Author: Nell Dale
language: en
Publisher: Jones & Bartlett Learning
Release Date: 2010-03-10
Revised and updated with the latest information in the field, the Fourth Edition of Computer Science Illuminated continues to engage and enlighten students on the fundamental concepts and diverse capabilities of computing. Written by two of today’s most respected computer science educators, Nell Dale and John Lewis, the text provides a broad overview of the many aspects of the discipline from a generic view point. Separate program language chapters are available as bundle items for those instructors who would like to explore a particular programming language with their students. The many layers of computing are thoroughly explained beginning with the information layer, working through the hardware, programming, operating systems, application, and communication layers, and ending with a discussion on the limitations of computing. Perfect for introductory computing and computer science courses, the fourth edition's thorough presentation of computing systems provides computer science majors with a solid foundation for further study, and offers non-majors a comprehensive and complete introduction to computing.
Exact Exponential Algorithms
Author: Fedor V. Fomin
language: en
Publisher: Springer Science & Business Media
Release Date: 2010-10-26
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.