Published:
2025, Proceedings of the 13th Workshop on Uncertainty Processing (WUPES’25) Tˇrešt’, Czech Republic, Praha, MATFYZPRESS, vydavatelství Matematicko-fyzikální fakulty UK), p. 152-163), ISBN 978-80-7378-525-3
Annotation:
Planning efficient tram schedules for municipal transportation presents significant challenges, often relying on time-consuming manual methods that struggle with network changes and complexity. This paper introduces a genetic algorithm-based heuristic approach to automate and optimize tram timetabling. The heuristic was evaluated on three selected subsets of the Prague tram network with different size. The largest example is a problem potentially computationally infeasible for nonheuristic approaches due to its vast combinatorial space. Results demonstrate that the proposed heuristic significantly accelerates the scheduling process, improves service levels by optimizing vehicle distribution and minimizing wait times, and reduces manual effort, offering a more efficient and adaptable tool for municipal transport planning.