Graph Theory And Combinatorial Optimization


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Handbook of Graph Theory, Combinatorial Optimization, and Algorithms


Handbook of Graph Theory, Combinatorial Optimization, and Algorithms

Author: Krishnaiyan Thulasiraman

language: en

Publisher: Chapman and Hall/CRC

Release Date: 2015-12-18


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This handbook provides comprehensive coverage of basic concepts and recent developments in the field. Focusing on design, proof of correctness, and complexity analysis, this volume presents a detailed discussion of algorithms that are useful in a variety of applications and offers an authoritative review of the current state of the art. Using figures to help illustrate the concepts, the book examines topics, such as incremental algorithms and online algorithms, that have yet to receive much attention but have great potential for future applications.

Graph Theory and Combinatorial Optimization


Graph Theory and Combinatorial Optimization

Author: David Avis

language: en

Publisher: Springer Science & Business Media

Release Date: 2005-12-06


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Graph theory is very much tied to the geometric properties of optimization and combinatorial optimization. Moreover, graph theory's geometric properties are at the core of many research interests in operations research and applied mathematics. Its techniques have been used in solving many classical problems including maximum flow problems, independent set problems, and the traveling salesman problem. Graph Theory and Combinatorial Optimization explores the field's classical foundations and its developing theories, ideas and applications to new problems. The book examines the geometric properties of graph theory and its widening uses in combinatorial optimization theory and application. The field's leading researchers have contributed chapters in their areas of expertise.

Combinatorial Optimization


Combinatorial Optimization

Author: Eugene Lawler

language: en

Publisher: Courier Corporation

Release Date: 2012-10-16


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Perceptive text examines shortest paths, network flows, bipartite and nonbipartite matching, matroids and the greedy algorithm, matroid intersections, and the matroid parity problems. Suitable for courses in combinatorial computing and concrete computational complexity.