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

By: Contributor(s): Material type: TextTextSeries: International series in pure and applied mathematicsPublication details: McGraw-Hill, c1993.ISBN:
  • 0075571013
Subject(s): DDC classification:
  • 511.5 20
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
Item type Home library Call number Status Date due Barcode Item holds
Two Week Loan 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.

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.

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.