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.
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.
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.