An Integrated Optimization-MCDA Framework for Efficient Electric Bus System Planning

The superior driving efficiency and reduced emissions of electric buses have been propelling the adoption of these vehicles in urban centers recently. However, transitioning from diesel to electric fleets presents numerous challenges, including fleet sizing and management, and charging infrastructure planning and operation. These issues complicate the decision-making process, especially given the variety of charging strategies (e.g., overnight charging, fast charging at terminal stations, and battery swap). This paper proposes a novel framework that integrates optimization and multi-criteria decision analysis (MCDA) to tackle the complexities related to planning and operating electric bus systems. The optimization model aims to minimize the capital and operational expenditures for different bus-system configurations. The results from the optimization model are then assessed using an MCDA approach, considering multiple and incommensurable criteria, to identify the best-ranked fleet configuration. In this context, this framework can aid planners to make more informed decisions in the transition to electric bus fleets.