Robust and Online Large-Scale Optimization

Models and Techniques for Transportation Systems

  • Ravindra K. Ahuja
  • Rolf H. Möhring
  • Christos D. Zaroliagis

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5868)

Table of contents

  1. Front Matter
  2. Robustness and Recoverability: New Concepts

    1. Christian Liebchen, Marco Lübbecke, Rolf Möhring, Sebastian Stiller
      Pages 1-27
    2. Serafino Cicerone, Gianlorenzo D’Angelo, Gabriele Di Stefano, Daniele Frigioni, Alfredo Navarra, Michael Schachtebeck et al.
      Pages 28-60
    3. Matteo Fischetti, Michele Monaci
      Pages 61-84
    4. Apostolos Bessas, Spyros Kontogiannis, Christos Zaroliagis
      Pages 85-118
    5. Anita Schöbel, Albrecht Kratz
      Pages 119-144
  3. Robust Timetabling and Route Planning

    1. Federico Barber, Laura Ingolotti, Antonio Lova, Pilar Tormos, Miguel A. Salido
      Pages 145-181
    2. Daniel Delling, Thomas Pajor, Dorothea Wagner
      Pages 182-206
    3. Daniel Delling, Dorothea Wagner
      Pages 207-230
    4. Matthias Müller-Hannemann, Mathias Schnee
      Pages 249-272
  4. Robust Planning under Scarce Resources

    1. Ángel Marín, Juan A. Mesa, Federico Perea
      Pages 273-292
    2. Michael Gatto, Jens Maue, Matúš Mihalák, Peter Widmayer
      Pages 310-337
    3. Guido Diepen, J. M. van den Akker, J. A. Hoogeveen
      Pages 338-353
  5. Online Planning: Delay and Disruption Management

    1. Holger Flier, Rati Gelashvili, Thomas Graffagnino, Marc Nunkesser
      Pages 354-368
    2. Francesco Corman, Rob M. P. Goverde, Andrea D’Ariano
      Pages 369-386
    3. Luzi Anderegg, Paolo Penna, Peter Widmayer
      Pages 387-398
    4. Julie Jespersen-Groth, Daniel Potthoff, Jens Clausen, Dennis Huisman, Leo Kroon, Gábor Maróti et al.
      Pages 399-421
  6. Back Matter

About this book


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.


Graph algorithms disruption management performance railway systems recoverable robustness reliability robust networks routing shortest path shunting subgraph coverage timetabling train disposition train traffic

Editors and affiliations

  • Ravindra K. Ahuja
    • 1
  • Rolf H. Möhring
    • 2
  • Christos D. Zaroliagis
    • 3
  1. 1.Department of Industrial & Systems EngineeringUniversity of FloridaGainesvilleUSA
  2. 2.Institut für MathematikTechnische Universität BerlinBerlinGermany
  3. 3.Department of Computer Engineering & InformaticsUniversity of PatrasPatrasGreece

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2009
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science Computer Science (R0)
  • Print ISBN 978-3-642-05464-8
  • Online ISBN 978-3-642-05465-5
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site