Szczegóły publikacji
Opis bibliograficzny
Mixed fleet bus scheduling with timetable shifting and vehicle-crew constraints: a real-world computational study / Jerzy DUDA, Marek KARKULA, Iwona SKALNA, Piotr Kisielewski, Adam Redmer // W: Transport Problems 2025 [Dokument elektroniczny] : XVII International Scientific Conference : [Katowice - Wisła - Žilina, 25-27.06.2025] ; XIV International Symposium of Young Researchers : [Katowice - Mysłowice, 23-24.06.2025] : proceedings. — Wersja do Windows. — Dane tekstowe. — [Katowice : Silesian University of Technology. Faculty of Transport and Aviation Engineering], [2025]. — 1 dysk optyczny. — e-ISBN: 978-83-975865-0-5. — S. 211–224. — Wymagania systemowe: Adobe Reader ; napęd CD-ROM. — Bibliogr. s. 223-224, Summ.
Autorzy (5)
- AGHDuda Jerzy
- AGHKarkula Marek
- AGHSkalna Iwona
- Kisielewski Piotr
- Redmer Adam
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 161422 |
|---|---|
| Data dodania do BaDAP | 2025-10-06 |
| Rok publikacji | 2025 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Politechnika Śląska |
Abstract
This paper addresses the significant challenge of scheduling electric bus fleets while integrating timetable flexibility with crew assignment constraints. We present an optimization framework for electric bus scheduling that incorporates timetable shifting strategies while adhering to crew operational constraints. We developed a mixed-integer linear programming (MILP) model that minimizes fleet size and operational costs while ensuring feasible crew assignments. The model captures essential fleet constraints, in particular electric vehicles, including battery capacity limitations and non-linear charging profiles. Our key contribution is a solution methodology that first optimizes vehicle scheduling with timetable flexibility, then ensures crew feasibility through constraint satisfaction techniques. Using real-world data from an urban transportation system, we conduct extensive computational experiments to evaluate the effectiveness of our approach. Results of our experiments demonstrate that strategic timetable shifting reduces fleet size and operational costs compared to fixed-timetable approaches, while satisfying real vehicle constraints and crew regulation requirements. Sensitivity analyses quantify the trade-offs between schedule flexibility, operational costs, and crew utilization. Our findings provide practical insights for transit operators transitioning to electric fleets, enabling efficient management of both vehicle and crew resources.
