Combinatorial Optimization and Graph Algorithms

Communications of NII Shonan Meetings

Nonfiction, Science & Nature, Mathematics, Discrete Mathematics, Computers, Database Management, Data Processing
Cover of the book Combinatorial Optimization and Graph Algorithms by , Springer Singapore
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9789811061479
Publisher: Springer Singapore Publication: October 2, 2017
Imprint: Springer Language: English
Author:
ISBN: 9789811061479
Publisher: Springer Singapore
Publication: October 2, 2017
Imprint: Springer
Language: English

Covering network designs, discrete convex analysis, facility location and clustering problems, matching games, and parameterized complexity, this book discusses theoretical aspects of combinatorial optimization and graph algorithms. Contributions are by renowned researchers who attended NII Shonan meetings on this essential topic. The collection contained here provides readers with the outcome of the authors’ research and productive meetings on this dynamic area, ranging from computer science and mathematics to operations research.

Networks are ubiquitous in today's world: the Web, online social networks, and search-and-query click logs can lead to a graph that consists of vertices and edges. Such networks are growing so fast that it is essential to design algorithms to work for these large networks. Graph algorithms comprise an area in computer science that works to design efficient algorithms for networks. Here one can work on theoretical or practical problems where implementation of an algorithm for large networks is needed. In two of the chapters, recent results in graph matching games and fixed parameter tractability are surveyed.

Combinatorial optimization is an intersection of operations research and mathematics, especially discrete mathematics, which deals with new questions and new problems, attempting to find an optimum object from a finite set of objects. Most problems in combinatorial optimization are not tractable (i.e., NP-hard). Therefore it is necessary to design an approximation algorithm for them. To tackle these problems requires the development and combination of ideas and techniques from diverse mathematical areas including complexity theory, algorithm theory, and matroids as well as graph theory, combinatorics, convex and nonlinear optimization, and discrete and convex geometry. Overall, the book presents recent progress in facility location, network design, and discrete convex analysis.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Covering network designs, discrete convex analysis, facility location and clustering problems, matching games, and parameterized complexity, this book discusses theoretical aspects of combinatorial optimization and graph algorithms. Contributions are by renowned researchers who attended NII Shonan meetings on this essential topic. The collection contained here provides readers with the outcome of the authors’ research and productive meetings on this dynamic area, ranging from computer science and mathematics to operations research.

Networks are ubiquitous in today's world: the Web, online social networks, and search-and-query click logs can lead to a graph that consists of vertices and edges. Such networks are growing so fast that it is essential to design algorithms to work for these large networks. Graph algorithms comprise an area in computer science that works to design efficient algorithms for networks. Here one can work on theoretical or practical problems where implementation of an algorithm for large networks is needed. In two of the chapters, recent results in graph matching games and fixed parameter tractability are surveyed.

Combinatorial optimization is an intersection of operations research and mathematics, especially discrete mathematics, which deals with new questions and new problems, attempting to find an optimum object from a finite set of objects. Most problems in combinatorial optimization are not tractable (i.e., NP-hard). Therefore it is necessary to design an approximation algorithm for them. To tackle these problems requires the development and combination of ideas and techniques from diverse mathematical areas including complexity theory, algorithm theory, and matroids as well as graph theory, combinatorics, convex and nonlinear optimization, and discrete and convex geometry. Overall, the book presents recent progress in facility location, network design, and discrete convex analysis.

More books from Springer Singapore

Cover of the book Arthropod Diversity and Conservation in the Tropics and Sub-tropics by
Cover of the book The Development of Service Economy by
Cover of the book Understanding the Impact of INSET on Teacher Change in China by
Cover of the book Advances in Manufacturing Processes by
Cover of the book Research into Design for a Connected World by
Cover of the book Defining and Measuring Economic Resilience from a Societal, Environmental and Security Perspective by
Cover of the book Acoustical Analysis of the Tanpura by
Cover of the book An Introduction to Python and Computer Programming by
Cover of the book Fundamental Fluid Mechanics and Magnetohydrodynamics by
Cover of the book Distributed Fusion Estimation for Sensor Networks with Communication Constraints by
Cover of the book Respiratory Endoscopy by
Cover of the book Smart Economy in Smart Cities by
Cover of the book Advances in GAPDH Protein Analysis: A Functional and Biochemical Approach by
Cover of the book Economics of Urban Externalities by
Cover of the book Knowledge Creation in Education by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy