Optimized Selection of Motorcycle Battery Swapping Stations Under Flexible Demand by Using Distance Function And Gis Technique

Abstract

Our research proposes an approach to finding a suitable location for a motorcycle Battery Swapping Station (BSS) that considers multiple objectives. We developed a model based on Euclidean distance with K-nearest neighbors (K-NN), the analytical hierarchy process (AHP) function, a desired number of stations, and geographic information system (GIS) based road infrastructure data. This model also considers the maximum coverage area and satisfies the number of stations and geographical features. Additionally, we consider the average driving distance of the battery swapping station location. To facilitate analysis, square grids form cells representing road type, environmental characteristics, places, and population density. Our proposed framework provides decision-makers with a multi-objective and visually optimized motorcycle BSS location, allowing for a more fiexible selection of exact BSS locations shown on a map. Our demonstration can be used to resolve the uncertain problem related to finding a place for a motorcycle battery swapping station location.