Applied and algorithmic graph theory / Gary Chartrand, Ortrud R. Oellermann.

By: Chartrand, GaryContributor(s): Oellermann, Ortrud RMaterial type: Text

TextSeries: International series in pure and applied mathematicsPublication details: McGraw-Hill, c1993. ISBN: 0075571013Subject(s): Graph theoryDDC classification: 511.5

Partial contents:

1. An Introduction to Graphs -- 2. An Introduction to Algorithms -- 3. Trees -- 4. Paths and Distance in Graphs -- 5. Networks -- 6. Matchings and Factorizations -- 7. Eulerian Graphs -- 8. Hamiltonian Graphs -- 9. Planar Graphs -- 10. Coloring Graphs -- 11. Digraphs -- 12. Extremal Graph Theory.

Summary: Designed as the bridge to cross the widening gap between mathematics and computer science, and planned as the mathematical base for computer science students, this discrete math text is written for upper-level college students who have had previous course work with proofs and proof techniques. The close tie between the theoretical and algorithmic aspects of graph theory, and the fact that graphs lend themselves naturally as models in computer science, result in a need for efficient algorithms to solve any large-scale problems. Each algorithm in the text includes explanatory statements that clarify individual steps, a worst-case complexity analysis, and algorithmic correctness proofs. As a result, the student will develop an understanding of the concept of an efficient algorithm.

Holdings ( 1 )
Title notes ( 4 )

Holdings
Item type	Home library	Call number	Status	Date due	Barcode	Item holds
Two Week Loan	College Lane Learning Resources Centre Main Shelves	511.5 CHA (Browse shelf(Opens below))	Available		4400476025

Total holds: 0

Enhanced descriptions from Syndetics:

Includes bibliographical references and index.

Designed as the bridge to cross the widening gap between mathematics and computer science, and planned as the mathematical base for computer science students, this discrete math text is written for upper-level college students who have had previous course work with proofs and proof techniques. The close tie between the theoretical and algorithmic aspects of graph theory, and the fact that graphs lend themselves naturally as models in computer science, result in a need for efficient algorithms to solve any large-scale problems. Each algorithm in the text includes explanatory statements that clarify individual steps, a worst-case complexity analysis, and algorithmic correctness proofs. As a result, the student will develop an understanding of the concept of an efficient algorithm.