Tactical optimization of urban bus fleet allocation using aggregate planning and discrete event simulation: a case study in Metropolitan Lima

Abstract

Urban public transport in Latin American cities has high operating costs and deficiencies in fleet management due to the absence of tactical planning based on real data. This study proposes a bus timetable allocation strategy through the integration of aggregate planning, optimization and discrete event simulation, applied to a real route in Metropolitan Lima. The methodology is structured in four stages: gathering operational information through focus groups, formulating the aggregate planning model, comparative evaluation of tactical strategies, and validation through simulation in ProModel. The results show that the pursuit strategy significantly reduces daily operating costs, moving from an oversized scheme to optimal fleet allocation without affecting service quality. The simulation confirms the operational stability of the system, showing controlled passenger flows and efficient use of resources. The proposal is replicable for urban transport companies with technological limitations and contributes to improving tactical decision-making in contexts of high demand variability.