given a 3d cube with a size of m x m x m, is there an efficient algorithm to find N integer points with the average Euclidean distance between each pair maximized? If not, is there any evolutionary approach I can take to this, so in each step the solution will be improved?


  • $\begingroup$ You'll get a pretty good solution if you choose $N$ points at random. $\endgroup$ – Yuval Filmus May 9 at 9:04

Note that maximizing the average distance between every pair of points is the same as maximizing the total distance between every pair of points.

Let's look at an m x m square first. When N = 4, it is clear that the optimal solution is placing a point in each corner.

For N = 5, the next picture explores two alternatives of placing the 5th point when the other 4 are in the corners. It appears it is optimal to place the 5th point also in a corner. Note that in the right picture, which is already sub-optimal, the total solution does not improve when moving any of the other four points (which are in the corners).

solution in a square

This solution does not work for all N, but it generalizes to cubes when N is a multiple of 8. Then all points are in the eight corners in an optimal solution.

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  • $\begingroup$ 1. For 5 points, it appears you are assuming that it is optimal to place 4 of the points in a corner. What if there is a better solution that does not involve having at least 4 points in a corner? 2. For cubes, you propose a solution when $N$ is a multiple of 8. How do you know that it is optimal, and that there is no better solution? $\endgroup$ – D.W. May 9 at 21:29
  • $\begingroup$ @D.W. I agree these "proofs" are sloppy, but I challenge anyone to find a counterexample to the claims. Indeed, in 2d for N=5 it is optimal to place all points in corners. In 2d it may only not hold for N = 3 mod 4. And in 3d when N is a multiple of 8, it is optimal to place all points in corners. $\endgroup$ – Albert Hendriks May 10 at 6:44

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