Ravindra K. Ahuja

Thomas L. Magnanti

James B. Orlin

An introduction to network flows discusses paths, algorithms, shortest paths, maximum flows, minimum cost flows, convex cost flows, generalized flows, and other topics

Theory, Algorithms, and Applications

Network Flows

Rolf H. Möhring

Christos D. Zaroliagis

Scheduled transportation networks give rise to very complex and large-scale networkoptimization problems requiring innovative solution techniques and ideas from mathematical optimization and theoretical computer science. Examples of scheduled transportation include bus, ferry, airline, and railway networks, with the latter being a prime application domain that provides a fair amount of the most complex and largest instances of such optimization problems. Scheduled transport optimization deals with planning and scheduling problems over several time horizons, and substantial progress has been made for strategic planning and scheduling problems in all transportation domains. This state-of-the-art survey presents the outcome of an open call for contributions asking for either research papers or state-of-the-art survey articles. We received 24 submissions that underwent two rounds of the standard peer-review process, out of which 18 were finally accepted for publication. The volume is organized in four parts: Robustness and Recoverability, Robust Timetabling and Route Planning, Robust Planning Under Scarce Resources, and Online Planning: Delay and Disruption Management.

Models and Techniques for Transportation Systems

Robust and Online Large-Scale Optimization

Bringing together the classic and the contemporary aspects of the field, this comprehensive introduction to network flows provides an integrative view of theory, algorithms, and applications. It offers in-depth and self-contained treatments of shortest path, maximum flow, and minimum cost flow problems, including a description of new and novel polynomial-time algorithms for these core models. For professionals working with network flows, optimization, and network programming.

Ravindra K. Ahuja

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