In order to solve the multi-objective optimization problem of the interference amount between the sealing ring and the dust cover of automotive transmission shaft bearing, an optimization design method for the interference amount of automobile transmission shaft bearings based on the generalized normal distribution optimization(GNDO) algorithm and multi-objective chimp optimization algorithm(MOChOA) is proposed. The digital piecewise linear chaotic map with perturbation is used to initialize the positions of chimp individuals, in order to reduce the blindness of early search, enhance the convergence speed of the MOChOA, and improve the optimization accuracy of the MOChOA. The GNDO is employed to conduct global exploration and local exploitation, and select the current best location, which reduces the probability of the MOChOA falling into local optima. The MOChOA searches for the Pareto optimal solution set, which provides various solutions for bearing designers. The experimental results show that the sealing performance of the optimized bearing has been greatly improved. The average value of the pollutant entry amount of the optimized bearings decreases by 77.78%.