There has been an explosive growth in the field of combinatorial algorithms. These algorithms depend not only on results in combinatorics and especially in graph theory, but also on the development of new data structures and new techniques for analyzing algorithms.
Four classical problems in network optimization are covered in detail, including a development of the data structures they use and an analysis of their running time.
Data Structures and Network Algorithms attempts to provide the reader with both a practical understanding of the algorithms, described to facilitate their easy implementation, and an appreciation of the depth and beauty of the field of graph algorithms.
Adopted for classroom use by Harvard University, Dartmouth University, the University of Chicago, the University of Colorado, Brown University, the University of Pennsylvania, Johns Hopkins University, and Princeton University (partial listing).