Optimizing layouts of initial AFV refueling stations targeting different drivers, and experiments with agent-based simulations

Zhao, J. & Ma, T. (2016). Optimizing layouts of initial AFV refueling stations targeting different drivers, and experiments with agent-based simulations. European Journal of Operational Research 249 (2) 706-716. 10.1016/j.ejor.2015.08.065.

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Abstract

The number of refuelling stations for AFVs (alternative fuel vehicles) is limited during the early stges of the diffusion of AFVs. Different layouts of these initial stations will result in different degrees of driver concern regardng refueling and will therefore influence dividuals' decisions to adopt AFVs. The question becomes "what is an optimal layout for these initial stations? Should it target all drivers or just a portion of them, and if so, which portion?" Further, how does the number of initial AFV refueling stations influence the adoption of AFVs? This paper explores these questions with agent-based simulations. Using Shanghai as the basis of computational experiments, this paper first generates different optimal layouts using a genetic algorithm to minimize the total concern of different targeted drivers and then conducts agent-based simulations on the diffusion of AFVs with these layout. The main findings of this study are that (1) targeting drivers in the city center can induce the fastest diffusion of AFVs if AV technologies are mature and (2) it is possible that a larger number of initial AFV refueling stations may result in slower diffusion of AFVs because these initial stations may not have sufficient customers to survive. The simulations can provide some insights for cities that are trying to promote the diffusion of AFVs.

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