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Sun, X., Yu, H. and Solvang, W.D. (2020) Solving the Location Problem of Printers in a University Campus Using p-Median Location Model and AnyLogic Simulation. In: Wang, Y., Martinsen, K., Yu, T. and Wang, K., Eds., IWAMA 2019: Advanced Manufacturing and Automation IX, Springer, Singapore, 577-584.
https://doi.org/10.1007/978-981-15-2341-0_72

has been cited by the following article:

• TITLE: A Cautionary Note on the Application of GIS in Spatial Optimization Modeling

  AUTHORS: Bin Zhou

  KEYWORDS: Spatial Optimization, GIS, Agent-Based Model, Covariance Function, Interpolation

  JOURNAL NAME: Journal of Geographic Information System, Vol.16 No.1, February 28, 2024

  ABSTRACT: Spatial optimization as part of spatial modeling has been facilitated significantly by integration with GIS techniques. However, for certain research topics, applying standard GIS techniques may create problems which require attention. This paper serves as a cautionary note to demonstrate two problems associated with applying GIS in spatial optimization, using a capacitated p-median facility location optimization problem as an example. The first problem involves errors in interpolating spatial variations of travel costs from using kriging, a common set of techniques for raster files. The second problem is inaccuracy in routing performed on a graph directly created from polyline shapefiles, a common vector file type. While revealing these problems, the paper also suggests remedies. Specifically, interpolation errors can be eliminated by using agent-based spatial modeling while the inaccuracy in routing can be improved through altering the graph topology by splitting the long edges of the shapefile. These issues suggest the need for caution in applying GIS in spatial optimization study.