Operations Research
A Branch-and-Cut Approach for Solving Railway Line-Planning Problems
Transportation Science
A Column-Generation Approach to Line Planning in Public Transport
Transportation Science
A route set construction algorithm for the transit network design problem
Computers and Operations Research
Robust Optimization for Empty Repositioning Problems
Operations Research
Robust and Online Large-Scale Optimization: Models and Techniques for Transportation Systems
Robust and Online Large-Scale Optimization: Models and Techniques for Transportation Systems
The Concept of Recoverable Robustness, Linear Programming Recovery, and Railway Applications
Robust and Online Large-Scale Optimization
Recoverable Robustness in Shunting and Timetabling
Robust and Online Large-Scale Optimization
Robust and Online Large-Scale Optimization
The modeling power of the periodic event scheduling problem: railway timetables-and beyond
ATMOS'04 Proceedings of the 4th international Dagstuhl, ATMOS conference on Algorithmic approaches for transportation modeling, optimization, and systems
An integrated methodology for the rapid transit network design problem
ATMOS'04 Proceedings of the 4th international Dagstuhl, ATMOS conference on Algorithmic approaches for transportation modeling, optimization, and systems
Models for fare planning in public transport
Discrete Applied Mathematics
Transit network design by Bee Colony Optimization
Expert Systems with Applications: An International Journal
Service-Oriented Line Planning and Timetabling for Passenger Trains
Transportation Science
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The problem of defining suitable lines in a public transportation system (bus, railway, tram, or underground) is an important real-world problem that has also been well researched in theory. Driven by applications, it often lacks a clear description, but is rather stated in an informal way. This leads to a variety of different published line planning models. In this paper, we introduce some of the basic line planning models, identify their characteristics, and review literature on models, mathematical approaches, and algorithms for line planning. Moreover, we point out related topics as well as current and future directions of research.