Evolutionary algorithms are the main and effective methods in solving multi-objective optimization problems (MOP). Based on the NSGA-Ⅱ algorithm studied and analyzed, we improved its crowding mechanism by introducing the Niche theory to expedite its convergence velocity and improve its convergence precision. The representative test functions show that the improvements have higher computational efficiency and can obtain a reasonable distributing solution; it can also maintain the solutions' diversity.