I am struggling with a fairly simple and natural geometric optimization problem, but I have not been able to find an obvious canonical method for solving it:
I am given a collection of $m$ axis-aligned rectangles in the unit square, and my goal is to find the optimal positions of a set of $k$ distinct axis-aligned rectangles with given dimensions such that none of the $m+k$ rectangles intersect, and the sum of distances between the centers of the $k$ rectangles are minimized. Distances between rectangles are measured with respect to the length of the shortest $L_1$ path that does not intersect another rectangle (so it's often larger than standard $L_1$ distance).
Is there a field of optimization or computational geometry that would deal with this? I don't even see an obvious way to formulate it as a mixed integer linear program, due to the presence of shortest paths.