I'm trying to perform a spatial clustering assignment by minimizing spatial distance while maximizing total weight within each cluster.
My data contains 3 columns and approximately 170 rows (example shown below)
AvgWeight lat long 87.799 33.888102 -84.29321 165.258 31.459666 -83.51083 148.733 44.916657 -97.11346 484.038 43.020762 -88.26852 74.175 39.849156 -75.18159 83.861 42.02933 -93.60966 235.524 36.022863 -79.77895
I'd like to be able to cluster all of my spatial locations together while also maximizing the sum of my
AvgWeight column within each cluster up to some adjustable constraint (Say 10,000 lbs).
My previous clustering experience has been limited to
R so I was hoping that there would be some sort of variation I could implement to redefine my problem to fit with that methodology. However, I'm not sure how to go about minimizing geographic distance while maximizing my weight variable. I'm open to any suggestions on alternative methodologies preferably ones which can be implemented with