Understand how to solve minimum-cost flows fast with double scaling
This book explains a family of algorithmic techniques for finding minimum-cost circulations and related transportation problems. It covers how scaling ideas improve running times and how different methods compare, including capacity scaling, cost scaling, and excess scaling. The text also shows how data structures like dynamic trees boost efficiency in practice.
Readers will learn the core ideas behind transforming circulation problems into transportation problems, the role of e-optimality, and how combining multiple strategies can yield strong theoretical guarantees. The book presents several time-bound analyses and discusses when certain approaches work best for sparse versus dense networks.
- Foundations of the minimum-cost circulation problem and its transportation equivalents
- Key scaling techniques and how they speed up computation
- How dynamic trees and related data structures influence performance
- Comparisons of algorithms to guide practical choices in network optimization
Ideal for readers of operations research, algorithm design, and applied computer science who want a clear, math-grounded view of modern flow optimization methods.