Optimizing layouts of initial refueling stations for alternative-fuel vehicles and experiments with agent-based simulations. (March 2016)

• Record Type: Journal Article
• Authors: Zhao, Jiangjiang; Ma, Tieju
• Is Part Of: Simulation. Volume 92:Number 3(2016:Mar.)
• Page Start: 251
• Page End: 266
• Publication Date: 2016-03
• Subjects: Layout -- alternative-fuel vehicle -- agent-based simulations -- genetic algorithm; Computer simulation -- Periodicals; 003.3
• DOI: 10.1177/0037549716629726
• Languages: English
• ISSNs: 0037-5497

Abstract

There are a limited number of initial refueling stations for AFVs (alternative-fuel vehicles). With different layouts for these initial refueling stations, potential AFV adopters will have different concerns regarding the availability of refueling facilities, which will result in different starting points for the diffusion of AFVs. This paper explores the issue of optimizing layouts of initial AFV refueling stations to provide a better starting point for the diffusion of AFVs. This paper first puts forward the optimization models in terms of minimizing drivers' total concern in two situations: in the first situation, the number of initial AFV refueling stations is fixed, and in the second situation, the number of initial AFV refueling stations is flexible within a certain scope. The paper then introduces a genetic algorithm to find nearly optimal solutions for the optimization models. Finally, experiments are conducted with agent-based simulations for the case of Shanghai, which shows that the close-to-optimal layouts generated using the models can promote the diffusion of AFVs.