In Clustering we want to find optimal Clusters - data points that are close together (measure by a defined distance measure). Is there any "Anti-"Clustering? We have a set of data points and want to find "Anti-"Clusters - subsets with data points that are as far apart as possible (measure by a defined distance measure, for example euclidean distance).
In a concrete application I have a set of people and want to divide these people into n groups as diverse as possible measure with a few predefined criteria (diverse means: as less as possible of the same values of each criteria in each group).
The first time I thought about this it seemed pretty intuitive but I couldn't find any method to create these subsets, maybe I'm to focused on regular Clustering methods. Sorry, if this question is too trivial, but any help would be appreciated!