A Hypervolume Contribution Approximation Method Based on Angular Points

In this paper, a hypervolume contribution approximation method is proposed. The main idea is to find out all angular points in the hypervolume contribution region of the solution by iteration and make an approximation by the distance of the line segment from angular points to reference points. The searching strategy is introduced first, and then the angular points elimination/compensation measures are proposed. In the experiment section, we introduce two state-of-the-art hypervolume contribution approximation methods for comparison with the proposed algorithm. These methods are tested on six different Pareto front solution sets. The results show that the proposed method has better performance than other methods. In particular, the proposed method is competitive in recognizing the hypervolume contribution of large-scale solution sets.