Combinatorial Algorithms: Generation, Enumeration, and Search (Discrete Mathematics and Its Applications) [Hardcover]

Donald L. Kreher (Author), Douglas R. Stinson (Author)

Book Description

ISBN-10: 084933988X | ISBN-13: 978-0849339882 | Publication Date: December 18, 1998 | Edition: 1

This textbook thoroughly outlines combinatorial algorithms for generation, enumeration, and search. Topics include backtracking and heuristic search methods applied to various combinatorial structures, such as:

Combinations

Permutations

Graphs

Designs

Many classical areas are covered as well as new research topics not included in most existing texts, such as:

Group algorithms

Graph isomorphism

Hill-climbing

Heuristic search algorithms

This work serves as an exceptional textbook for a modern course in combinatorial algorithms, providing a unified and focused collection of recent topics of interest in the area. The authors, synthesizing material that can only be found scattered through many different sources, introduce the most important combinatorial algorithmic techniques - thus creating an accessible, comprehensive text that students of mathematics, electrical engineering, and computer science can understand without needing a prior course on combinatorics.

Product Details

• Hardcover: 344 pages
• Publisher: CRC Press; 1 edition (December 18, 1998)
• Language: English
• ISBN-10: 084933988X
• ISBN-13: 978-0849339882
• Product Dimensions: 9.5 x 6.4 x 0.9 inches
• Shipping Weight: 1.4 pounds (View shipping rates and policies)
• Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
• Amazon Best Sellers Rank: #797,412 in Books (See Top 100 in Books)

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Most Helpful Customer Reviews

27 of 28 people found the following review helpful:

5.0 out of 5 stars An engaging and useful text on an important topic., June 12, 1999

By A Customer

This review is from: Combinatorial Algorithms: Generation, Enumeration, and Search (Discrete Mathematics and Its Applications) (Hardcover)

Combinatorial algorithms are widely used in a diverse set of applications areas from engineering, the biological and physical sciences, mathematics and computation, economics, and so on. In addition to their applied nature, combinatorial algorithms often rely on sophisticated results in combinatorics and algebra and on clever data structures. This makes the task of introducing the multi-faceted world of combinatorial algorithms a difficult one.

Kreher and Stinson have written a modern text that addresses the subject systematically, and from a variety of viewpoints. Their text is engaging and accessible to a senior undergraduate student. Nevertheless, a researcher will also find the text informative and useful. It provides an excellent balance of mathematical background, algorithm development, and algorithm implementation. The book has been designed to support an undergraduate course, and provides further material to support a more intensive graduate level course. The text has well designed chapter notes and exercises; the presentation of the methods through description, pseudocode, and examples is particularly clear. However, it is the selection of topics that makes this text especially good.

Numerous strong texts on graph algorithms are concerned with the analysis of properties of graphs rather than the generation and search for combinatorial objects. Highly structured combinatorial objects, such as error-correcting codes or interconnection networks, are notoriously difficult to find via computational methods. The authors develop a powerful toolkit of algorithms for addressing generation and search problems. They start with simple tools and then use these along with some basic combinatorial mathematics to build quite sophisticated tools. The text provides enough information to develop and understand each of the algorithms presented, and enough pointers for the interested reader to find more.

This is an excellent book. I enjoyed reading it. More importantly, there is no doubt that an interesting course can be taught from this book at either the undergraduate or graduate level. There is enough flexibility in the choice of material and emphasis to support a course on mathematical aspects, algorithmic techniques, or applications.