I have a locus L
of points (lat, long). And I would like to find N=10 points (let's call them warehouses) such that:
$$loss = \sum_{l \in L} maximum_{w \in W}(distance(l, w))^2 $$
is minimized.
Is there a documented algorithm or approach that solves this problem? Right now I am thinking Excel may be able to handle this task. However I have too much data for Excel and will need to implement this in Python / Pandas.