Synopsis
Explore the core ideas behind network optimization and how they shape real-world decision making. This accessible guide introduces the fundamental network flow models, their key properties, and the algorithmic ideas that drive modern optimization practice. Readers will gain a clear view of why networks matter in planning, scheduling, and design. Network Flows explains how a directed network can model costs, capacities, and supplies, and shows how simple constraints lead to powerful results. The book emphasizes practical algorithms and how they solve classic problems like shortest paths, maximum flows, and minimum-cost flows, with an eye toward both theory and real-world use.
- Foundational models and the math behind network flows, including incidence matrices and balance constraints
- Popular problem families: shortest path, maximum flow, minimum-cost flow, and assignment problems
- Key algorithms with practical efficiency and polynomial-time behavior
- Connections to applications in physical networks, routing, scheduling, and network design
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