Robust and Online Large-Scale Optimization

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
• quality control, reliability, safety and risk
• combinatorics

• Department of Industrial & Systems Engineering, University of Florida, Gainesville, USA

  Ravindra K. Ahuja

• Institut für Mathematik, Technische Universität Berlin, Berlin, Germany

  Rolf H. Möhring

• Department of Computer Engineering & Informatics, University of Patras, Patras, Greece

  Christos D. Zaroliagis

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