Optimizing Travel Time and Regenerative Energy for Periodic Timetables
This work addresses the trade-off between energy efficiency and passenger convenience in railway timetable design, providing a theoretical foundation and practical insights for operators.
The authors formulate a bicriteria optimization problem to design periodic railway timetables that maximize regenerative energy usage while minimizing passenger travel time. They prove NP-hardness for a single objective but identify polynomial-time solvable special cases, and validate their model with case studies showing practical Pareto fronts.
Regenerating braking energy is one major pathway to make rail traffic energy-efficient. It is therefore desirable to design timetables that exploit this feature. However, timetables that allow to regenerate energy are often bad for the passengers. We hence formulate and analyze a bicriteria optimization problem (PESP-Passenger-Energy) to find periodic railway timetables that maximize the regenerated energy in terms of the brake-traction overlap time and minimize the travel time of the passengers. Our model extends the Periodic Event Scheduling Problem (PESP) and offers a rich combinatorial theory. We investigate its computational complexity on one-station networks, building on matchings and Hamiltonian paths. Besides showing its NP-hardness even for a single objective, we identify several polynomial-time solvable special cases. Finally, we provide two case studies, underlining the practicability of our model, and analyzing the Pareto front.