Yangming and Jin-Kao Hao. An iterated local search algorithm for the minimum differential dispersion problem. Knowledge-based Systems 125: 26-38, 2017. http://dx.doi.org/10.1016/j.knosys.2017.03.028

The source code of our proposed ILS_MinDiff algorithm is available
in here.

Please make sure that the above paper is cited if you use the code in
your research. The software is distributed for academic puposes only. If you
wish to use this software for commercial applications, please obtain a
permission from Yangming Zhou (zhou.yangming@yahoo.com or yangming@info.univ-angers.fr) or Jin-Kao Hao (jin-kao.hao@univ-angers.fr).
### Problem
definition

*Given a set of n elements separated by a pairwise distance matrix,
the ***minimum differential dispersion problem (Min-Diff DP)** aims to
identify a subset of m elements (m < n) such that the difference between the
maximum sum and the minimum sum of the inter-element distances between any two
chosen elements is minimized.

### Instance
files

**MDPLIB** provides a comprehensive set of
instances which are widely used for testing algorithms for diversity and
dispersion problems, and it is available at **http://www.optsicom.es/mindiff/**. By excluding the small and easy instances, the
remaining 190 benchmark instances tested in this work include the following six
datasets: SOM-b, GKD-b, GKD-c, MDG-a, MDG-b and MDG-c.