Exact hypervolume subset selection through incremental computations
Andreia P. Guerreiro, Vasco M. Manquinho, José Rui Figueira · Computers & Operations Research · 2021
The (environmental) selection procedure in Evolutionary Multiobjective Optimization Algorithms (EMOAs) can be interpreted as a subset selection problem, where the goal is to determine a subset of a given size that maximizes a quality indicator. The hypervolume indicator possesses desirable theoretical properties (e.g. monotonicity properties) that make it well-suited for indicator-based selection, and SMS-EMOA is a good example of this. In such a case, selection is viewed as a Hypervolume Subset Selection Problem (HSSP) that consists of selecting a subset of k points from a set of n points that maximizes the hypervolume indicator. However, apart from SMS-EMOA that considers the case of k=n−1, HSSP-based selection in EMOAs with more than 2 objectives and k