Memetic self-adaptive evolution strategies applied to the maximum diversity problem

The Maximum Diversity Problem (MDP) consists in finding a subset of elements which have maximum diversity between each other. It is a very important problem due to its general aspect, that implies many practical applications such as facility location, genetics, and product design. We propose a method based on Evolution Strategies (ES) with Local Search and SelfAdaptation of the parameters. For all time limits from 1 to 300 seconds as well as for time to converge to the best solutions known, this method leads to better results when compared to other state-of-the-art algorithms.