Michael Holzhauser discusses generalizations of well-known network flow and packing problems by additional or modified side constraints. By exploiting the inherent connection between the two problem classes, the author investigates the complexity and approximability of several novel network flow and packing problems and presents combinatorial solution and approximation algorithms.
Fractional Packing and Parametric Search Frameworks.- Budget-Constrained Minimum Cost Flows: The Continuous Case.- Budget-Constrained Minimum Cost Flows: The Discrete Case.- Generalized Processing Networks.- Convex Generalized Flows.
Dr. Michael Holzhauser studied computer science at the University of Kaiserslautern and is now a research fellow in the Optimization Research Group at the Department of Mathematics of the University of Kaiserslautern.
Michael Holzhauser discusses generalizations of well-known network flow and packing problems by additional or modified side constraints. By exploiting the inherent connection between the two problem classes, the author investigates the complexity and approximability of several novel network flow and packing problems and presents combinatorial solution and approximation algorithms.
Contents
- Fractional Packing and Parametric Search Frameworks
- Budget-Constrained Minimum Cost Flows: The Continuous Case
- Budget-Constrained Minimum Cost Flows: The Discrete Case
- Generalized Processing Networks
- Convex Generalized Flows
Target Groups
- Researchers and students in the fields of mathematics, computer science, and economics
![Generalized Network Improvement and Packing Problems [Paperback]](/itemImage/2/5/8/7/2_1002194.jpg)