FACULTY AND RESEARCH

The motivation of this study is to minimize the system-level travel time costs and greenhouse emissions, which include tailpipe emissions by internal combustion engine vehicles (ICEVs) and smokestack emissions indirectly caused by electric vehicles (EVs), while satisfying EVs’ replenishment need in transport networks subject to financial restraints for infrastructure development. In this study, we address recharge facility locations of EVs, where two types of recharge services are taken into account, that is, traditional charging stations and modern charging lanes. The multitype recharge facility location problem is formulated by employing the bilevel framework of the network design problem. In the lower-level program, the mixed-vehicular traffic assignment problem with en-route multitype recharge is employed, which accounts for both ICEVs and EVs with various driving ranges. The upper-level program aims to minimize the total system travel costs by selecting the optimal solution from a set of infrastructure design options considering both expansions of road capacities and provisions of multitype recharge facilities for EVs. In the algorithmic framework, we propose a tailored metaheuristic to solve medium to large instances. Systematic evaluation is conducted to test the efficacy of the proposed approach. The results highlight the impacts of traffic composition, distance ranges of EVs, budget levels and facility expenses on the project selection and evaluation. The results indicate that the two design objectives, to respectively minimize the network-wide travel time and greenhouse emissions, are conflicting for certain scenarios. Additionally, the results demonstrate the advantages of the network design problem (NDP) considering both multitype recharge service provision and road capacity enhancement over the NDP accounting for the former only.