MaOEA/APP-PBI: a many-objective evolutionary algorithm based on adaptive projection plane and PBI function

Many-objective optimisation challenges traditional Pareto-based evolutionary algorithms. This work introduces a self-adjusting dominance relation using an adaptive projection plane, enhancing convergence by leveraging distances to the plane and between projection points without extra parameters. It also proposes a PBI-function-based method to balance convergence and diversity in solution screening. These techniques are integrated into the NSGA-II framework, creating the MaOEA/APP-PBI algorithm. Evaluated on 5-, 10-, 15-, and 20-objective DTLZ and WFG problems using IGD and HV metrics, MaOEA/APP-PBI outperforms six leading algorithms. Results demonstrate its significantly superior convergence and diversity across various objectives, highlighting its effectiveness for many-objective optimisation.