Minimizing Energy Use of Mixed-Fleet Public Transit for Fixed-Route Service

Affordable public transit services are crucial for communities since they enable residents to access employment, education, and other services. Unfortunately, that provide wide coverage tend suffer from relatively low utilization, which results in high fuel usage per passenger mile, leading operating costs environmental impact. Electric vehicles (EVs) can reduce energy impact, but most agencies have employ them combination with conventional, internal-combustion engine due the upfront of EVs. To make best use such a mixed fleet vehicles, need optimize route assignments charging schedules, presents challenging problem large networks. We introduce novel formulation minimize electricity by assigning trips scheduling charging, while serving an existing fixed-route schedule. present integer program optimal assignment scheduling, we propose polynomial-time heuristic meta-heuristic algorithms larger evaluate our on service Chattanooga, TN using operational data collected vehicles. Our show proposed scalable and, hence, impact costs. For save $145,635 576.7 metric tons CO2 emission annually.