Although a variety of many-objective evolutionary algorithms have been proposed, the difficulty in balancing the convergence and diversity of the population still remains. To address this issue, we proposes an indicator selection and density estimation deletion-based many-objective evolautionary algorithm(MaOEA/IS-DED). In this algorithm, the selection strategy based on the $I_{\varepsilon+