Robust electric transit route network design problem (RE-TRNDP) with delay considerations: Model and application

•Opportunity charging electric bus network design under power supply variability.•Robust Optimization coupled with Multi-Objective Particle Swarm Optimization.•En-route charging delays and queue formation at terminal stops considered.•The relative cost of robustness is higher under investment cost minimization.•Charging scheme at terminal stops affects the spread of the Pareto front. Electric bus networks are steadily gaining ground as the prominent option for urban public transport. However, in contrast to conventional transit systems operated by diesel buses, electric bus networks are particularly vulnerable with respect to energy supply, both in terms of power level availability and the unobstructed access to charging points. Indeed, power fluctuations can prevent buses from adequately recharging at designated points, affecting extended areas of operation. Similarly, queue formation at terminal stops can lead to poor schedule adherence and excessive delays. In this context, this study addresses research gaps by presenting a realistic and flexible design framework for fully electric public transport networks, tackling both the route network and the charging infrastructure design. To handle the uncertainty associated with power supply, Robust Optimization (RO) is employed for solving the charging infrastructure location problem while maintaining computational tractability. Queuing delays due to charging are also modeled and minimized. To address the integrated design of route networks and wireless chargers, RO is coupled with Multi-Objective Particle Swarm Optimization within a bi-level methodological framework. Different scenarios for power supply variability are considered. Results show that depending on policy priority, the cost of robustness significantly changes.