New heuristics for the maximum diversity problem

The Maximum Diversity Problem (MDP) consists in identifying, in a population, a subset of elements, characterized by a set of attributes, that present the most diverse characteristics between themselves. The identification of such solution is an NP-hard problem. Some heuristics are available to obtain approximate solutions for this problem. In this paper we propose different GRASP heuristics for the MDP, using distinct construction procedures and path-relinking techniques. Performance comparison between related work and the proposed heuristics is provided. Experimental results show that the new GRASP heuristics are quite robust and are able to find high-quality solutions in a feasible computational time.