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Generalized Network Improvement and Packing Problems [electronic resource] / by Michael Holzhauser.

By: Contributor(s): Material type: TextTextPublisher: Wiesbaden : Springer Fachmedien Wiesbaden : Imprint: Springer Spektrum, 2016Description: XVI, 213 p. 26 illus. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783658168124
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 519.6 23
LOC classification:
  • QA402.5-402.6
Online resources:
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.
In: Springer eBooksSummary: 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 Practitioners in operations research and logistics The Author 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.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
E-BOOKS ISI Library, Kolkata Not for loan EB1736
Total holds: 0

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.

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 Practitioners in operations research and logistics The Author 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.

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