This research develops and applies a mixed-integer linear programming model that optimizes the locations of fueling stations considering not only the limited driving range of vehicles but also the necessary deviations that drivers are likely to make from their shortest paths in order to refuel their vehicles when the refueling station network is sparse. The Deviation-Flow Refueling Location Model (DFRLM) locates facilities to maximize the total flows refueled on deviation paths. The flow demand captured by the stations is assumed to decrease as the deviation that drivers must make increases. Test results indicate that the maximum allowable deviation and the specific deviation penalty functional form do have a measurable effect on the optimal locations of facilities and objective function values as well.
ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment
- Fuel Technology
- Condensed Matter Physics
- Energy Engineering and Power Technology