Synopses & Reviews
This is a textbook on graph theory, especially suitable for computer scientists but also suitable for mathematicians with an interest in computational complexity. Although it introduces most of the classical concepts of pure and applied graph theory (spanning trees, connectivity, genus, colourability, flows in networks, matchings and traversals) and covers many of the major classical theorems, the emphasis is on algorithms and thier complexity: which graph problems have known efficient solutions and which are intractable. For the intractable problems a number of efficient approximation algorithms are included with known performance bounds. Informal use is made of a PASCAL-like programming language to describe the algorithms. A number of exercises and outlines of solutions are included to extend and motivate the material of the text.
Synopsis
An introduction to pure and applied graph theory with an emphasis on algorithms and their complexity.
Synopsis
Algorithm Graph Theory introduces most of the classical concepts of pure and applied graph theory (spanning trees, connectivity, genus, colourability, flows in networks, matching and transversals) and covers many of the classical theorems. Its emphasis is on algorithms and their complexity ñwhich graph problems have known efficient solutions and which are intractable.
Synopsis
This introduction to most of the classical concepts of pure and applied graph theory covers many of the major classical theorems. The emphasis is on algorithms and their complexity--what graph problems have known efficient solutions and which are intractable.
Table of Contents
Preface; 1. Introducing graphs and algorithmic complexity; 2. Spanning-trees, branchings and connectivity; 3. Planar graphs; 4. Networks and flows; 5. Matchings; 6. Eulerian and Hamiltonian tours; 7. Colouring graphs; 8. Graph problems and intractability; Appendix; Author Index; Subject Index.