Title
Evaluate Errors of 1-median Model: A Case Study in Spring Hill, FL, US
Abstract
Where to establish new facilities has received an increasing focus among researchers. Approaches to this question depend on at least a set of three elements, namely representation of demand units, a distance metric, and a location-allocation model. Yet, the choice of these parameters may potentially generate different results leading to significant location errors. The aim of this paper is to quantify the impacts of demand units and distance metric on final location-allocation layout by applying the L-median model to locate one new facility in Spring Hill, Florida, and then provide reference when making the allocation decisions through presenting a picture to illustrate how significant the error is when different decisions are made. The results indicate that distance metric is the most significant factor. Among the four examined metrics, the closest-point distance performs the best than other metrics. On the other hand, the representation of demand units plays a less important role in our case. This research provides guidance on appropriate selection of parameters in location-allocation analysis. One conclusion is that fine demand units are adapted to accurate distance metrics, while coarse demand units to less accurate distance metrics.
Year
DOI
Venue
2018
10.1109/GEOINFORMATICS.2018.8557195
2018 26th International Conference on Geoinformatics
Keywords
Field
DocType
Location allocation,spatial units,distance metric
Data mining,Location-allocation,Computer science,Metric (mathematics)
Conference
ISSN
ISBN
Citations 
2161-024X
978-1-5386-7620-2
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Jin Ye1207.71
Yujie Hu221.05
Xianrui Xu341.47
Hong Yi413.41
Xiang Li511011.84