A knee point-driven many-objective pigeon-inspired optimization algorithm

Abstract The number of solutions obtained is too large to provide a set with good performance in the nearby area true Pareto front when problem-specific preferences are unavailable. Therefore, this paper proposes knee point-driven many-objective pigeon-inspired optimization algorithm (KnMAPIO). An environmental selection strategy based on knee-oriented dominance proposed improve pressure and population diversity. In addition, new velocity updating equation Gaussian distribution, Cauchy distribution Levy search directions reduce possibility falling into local optima. Two types experiments carried out paper: one compare method four other algorithms benchmark PMOPs verify algorithm’s detecting points region; another eight state-of-the-art classic DTLZ WFG. results both effectiveness ability approximate front.