Algorithms for multi-stage optimization problems: Integrated optimization for public transport

• Applicant: Professorin Dr. Anita Schöbel
• Subject Area: Theoretical Computer Science ; Mathematics ; Traffic and Transport Systems, Intelligent and Automated Traffic
• Term: from 2015 to 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 238487308

This project analyzes multi-stage optimization problems with emphasis on integrated planning in public transportation as test case. We consider stop location, line planning, timetabling, and vehicle scheduling. We analyze the integrated planning process as a whole. The focus will be on robust planning in integrated optimization. One goal is to analyze in which stage of a sequential process robustness issues are best to be considered.A second focus delivers research on making models and procedures applicable for real-world instances. We deal with the integration of realistic passenger routing models, and we take capacities of vehicles and the first and last mile of the passengers into account. We plan to develop a pragmatic approach that is based on the Eigenmodel which we developed in the first part of this project. Using decomposition approaches we furthermore work on algorithms which allow simultaneous planning for peak and non-peak hours.Looking into future developments, such as mobile apps, we also want to discuss the question if periodicity of schedules is still needed. We plan to investigate which lines should be served with a periodic schedule and which can be served by small vehicles using dial-a-ride or similar procedures.All results will be tested and evaluated on benchmark instances.

• DFG Programme: Research Units
• Subproject of: FOR 2083: Integrated Planning for Public Transportation