Contributor
Rongbo Xu

[PySAL - spopt Development] P-Median Model with Near-Far Cost Allocation: Guided by Tobler's Law


Mentors
Levi John Wolf, James Gaboardi, Serge Rey, Qunshan Zhao, Germano Barcelos dos Santos
Organization
NumFOCUS
Technologies
python
Topics
Spatial data modelling
For now spopt has implemented several basic facility location models, providing the free open source for researcher, or organizations to use. However, there are still many useful improvements can be made. This proposal suggests improving the spopt package by implementing the P-Median model with Near-Far Cost Allocation. In the article by Church (2018), it proposed a new p-median model which can distinguish between near and far facilities, use both explicit and implicit variables for capacity allocations. Based on that, the writer plans to implement the p-median model with near-far cost allocation. By this, the spopt package can provide more accurate and efficient solutions to spatial optimization problems, typically for the problems with large data points, and large demand volume. This proposal will introduce the reason why the writer chooses this project, the technical details of this project, and the plan and delivery schedules.