Algorithm for fitting abstract distances in 2D

Question

Suppose we are given a small number of objects and "distances" between them -- what algorithm exists for fitting these objects to points in two-dimensional space in a way that approximates these distances?

The difficulty here is that the "distance" is not distance in Euclidean space -- this is why we can only fit/approximate.

(for those interested in what the notion of distance is precisely, it is the symmetric distance metric on the power set of a (finite) set).

Answer 1

Given that the number of objects is small, you can create an undirected weighted graph, where these objects would be nodes and the edge between any two nodes has the weight that corresponds to the distance between these two objects. You end up with n*(n-1)/2 edges.

Once the graph is created, there are a lot of visualization software and algorithms that correspond to graphs.