TOPIC
This study addresses the scalability challenges of the Mixed-Fleet Multi-Terminal Electric Bus Scheduling Problem by applying various heuristics and metaheuristics to urban-scale instances. A novel Repeated Local Search (RLS) is developed to handle full-day scenarios, considering fleet assignment, charging activities, and deadheading costs while accounting for limited charging infrastructure. The RLS generates greedy feasible schedules for mixed fleets of electric and hybrid buses, serving as the foundation for two metaheuristics: Simulated Annealing (SA) and a Genetic Algorithm (GA). SA is adapted into two variants—one using Mixed-Integer Linear Programming (MILP)-based moves and another with RLS-based moves for rescheduling trip chains. The GA applies repair rules to correct infeasible solutions during crossover. The research follows a three-step experimental framework: stress-testing a MILP model, comparing it with metaheuristics on small-scale instances, and analyzing metaheuristics across various scenario sizes. Real-world urban-scale scenarios from Luxembourg City’s public transit network are used, featuring 1084 trips, 12 terminals, and 10 bus lines. Results show that the proposed methods perform comparably to model-based formulations in smaller instances, with substantial scalability improvements. Each algorithm demonstrates specific strengths, making the choice of method dependent on the scenario and computational needs. The findings suggest that, as bus fleets increasingly adopt electric power, the relative benefits for transit operators may diminish in larger urban contexts.
ABOUT THE LECTURER
Dr. Tommaso Bosi holds a Ph.D. in Computer Science and Automation from the University of Roma Tre, where he also represented Ph.D. students in the Department of Engineering. His academic background includes a master’s degree in Management and Automation Engineering. Dr. Bosi's research focuses on applying Operations Research, Machine Learning, and Big Data to sustainable transportation systems, exploring areas such as ICT system management and Fuzzy Logic. He has collaborated with corporate and academic institutions, including Trenitalia, CFL, Roma Tre, La Sapienza, the University of Luxembourg, TU Delft, and Beijing University. Dr. Bosi is an active member of AIRO (Italian Operational Research Association) and contributes to the Transport and Sustainability Working Groups within EURO (Association of European Operational Research Societies). In addition to his academic work, he serves as the Innovation Manager at RDC Research & Development Consulting Srl and is the scientific-educational coordinator for ITS ECO-STEM Generation. He is also a founding member and European Projects Manager for the Aless Don Milani foundation.