presents in-depth, self-contained treatments of shortest path, maximum flow, and minimum cost flow problems, including descriptions of polynomial-time algorithms for these core models.
emphasizes powerful algorithmic strategies and analysis tools such as data scaling, geometric improvement arguments, and potential function arguments.
provides an easy-to-understand descriptions of several important data structures, including d-heaps, Fibonacci heaps, and dynamic trees.
devotes a special chapter to conducting empirical testing of algorithms.
features over 150 applications of network flows to a variety of engineering, management, and scientific domains.
contains extensive reference notes and illustrations.