Representation and management of multiobjective evolutionary algorithm populations based on graphs

Until now, in the literature, little attention has been paid to the storage and handling of populations of multiobjective evolutionary algorithms (MOEAs). In this work, we present a new tool for representing and managing populations of MOEAs by means of the use of graphs that keep the information on the relations among the individuals of the population. In the paper, we establish the theoretical basis of this sort of graph. In addition, we develop algorithms for its construction and updating (addition and removal of individuals in the population), analyzing their theoretical complexities. We also study several aspects of their practical behaviour including storage requirements, time needed for the construction and the management of these graphs. Finally, we present a selection process time comparison with and without the proposed methodology.