Optimal mixed fleet and charging infrastructure planning to electrify demand responsive feeder services under stochastic demand

This paper addresses the joint optimization of fleet size and charging infrastructure planning for a demand-responsive feeder service under stochastic demand and a targeted CO2 emission reduction policy. The problem is formulated as a bi-level optimization problem where the up-per-level determines charging station configuration given stochastic demand patterns whereas the lower-level solves a mixed fleet dial-a-ride routing problem under the CO2 emission and capacitated charging station constraints considering also partial recharge options. An efficient deterministic annealing metaheuristic is proposed. The results show that the good performance of the algorithm. The preliminary results for the bi-level optimization problem with 50 requests highlighted the trade-off between the decisions of different components (mixed fleet size, charging station configuration and targeted CO2 reduction levels).