Optimization of Electric Bus Fleet Deployment Using Football Optimization Algorithm: A Case Study in Cuenca, Ecuador

This study evaluates the feasibility of electrifying the urban public transport system in Cuenca, Ecuador, through an approach that combines real data acquisition, dynamic-energy modeling, and optimization. Position (latitude, longitude, altitude) and speed data were collected across 35 urban routes to calculate longitudinal forces, energy consumption, and the state of charge of a reference electric bus. Based on this analysis, the avoided CO₂ emissions resulting from replacing diesel buses were estimated. To optimize the allocation of electric units, the Football Optimization Algorithm was implemented, formulated as a maximization problem of avoided CO₂ under capital investment and fleet-size constraints. Results show that the electrification of 150 buses, with an investment of USD 60 million, can reduce approximately 467 kg of CO₂ per day, prioritizing high-consumption routes such as lines 16, 21, and 27. The FOA demonstrated fast and stable convergence in fewer than 100 iterations, strategically distributing units to maximize environmental impact and cost-effectiveness. The proposed methodology provides a replicable framework for other Latin American cities with similar geographic and operational conditions, supporting decision-making for sustainable urban mobility.