| Summary: | 碩士 === 國立澎湖科技大學 === 服務業經營管理研究所 === 96 === Under the pressure of the greenhouse effect and the high price of
petroleum, promoting alternative-fuel vehicles is an important subject. The goal of this research is to establish an alternative-fuel refueling facility location model to economically locate the refueling stations, which simultaneously serve the flow-type and fixed-point demand. That is the determinations of alternative fuel refueling facility locations must ensure that alternative-fuel
vehicles can achieve their paths from the points of origins to destinations and returning to the origins, and also cover traffic demands within a station’s service area. The models being established are based on the developed alternative-fuel refueling-facility location model proposed by Lin (2007) (only the flow-type demands being considered). The single-objective model (minimum locating cost) is formulated by adding the constraints of set covering to the Lin’s model for serving the flow-type and fixed-point traffic demand using the minimized number of stations being sited, while the duel-objectives’ model (minimum locating cost and maximum covering of population) is established by adding the constraints of maximum covering to the Lin’s model for serving all flow-type demands and part of fixed-points’ demands (maximum covering) using the stations determined by the weights setting on each objective. To demonstrate the applicability of the proposed models, an empirical study regarding the planning of refueling stations for the alternative-fuel vehicles in Taiwan Island was conducted. In terms of the single objective model, we can find that the number of stations being sited will depend on the vehicle range and station’s covering scope/area. For example, with the range of 400 km and station’s covering distance of 60 km, 7 stations will be needed to serve all the type of demands. When the range is reduced to 200 km and covering scope remains the same, the numbers increase to 11. If the covering scope is further reduced to 30 km, total stations being sited are up to 15. In terms of the duel objective model, different solutions can be obtained by using different weights on each objective and then demonstrates the relationship of the trade-off between the number of the stations being sited and
the population being covered. For example, with the range of 250 km and the serving scope of 30 km, 8 stations is needed to serve all the flow-type demands and meantime the population of 12189419 at fixed-points is covered for the weight of 1 being set on minimum-cost objective. If the weight on the objectives of minimum locating cost and maximum covering of population are 0.25 and 0.75 respectively, 9 stations are needed to serve all flow-type demands
and the population of 20767531 is covered. Therefore, multiple inferior solutions can be obtained and referenced by the decision makers such as investors of refueling facility.
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