A Metanetwork-based Optimization Approach to Locating Charging Stations for Electric Vehicles in Highway Networks
This paper presented a station-subpath metanetwork-based approach for modeling and solving the optimal charging infrastructure location problem.Specifically,this paper proposed a two-phase mixed linear integer programming model,and accordingly developed a two-phase algorithm powered by the branch-and-bound method,decomposing any individual routing-charging decision into two phases.The first phase aimed to find the distance-constrained minimum-cost subpath between each charging station pair in the original network,which was handled by the bi-criterion label-correcting algorithm;while the main algorithmic step of the second phase was to,in the branch-and-bound framework,repeatedly identified the minimum-cost path between each origin-destination pair in the metanetwork,which can be efficiently solved by the classic single-criterion label-setting algorithm.The numerical results from applying the developed metanetwork-based approach for the Yangtze River Delta network reveal that the construction budget limit of charging stations and driving range limit of electric vehicles play important roles in charging station location decisions and individual route-and-charge choices.When applied to three different sizes of numerical networks,the metanetwork-based approach proposed in this paper exhibits dominantly higher computational efficiency than the conventional network-based approach for this type of problems of large size.
万方数据
维普
