Abstract: In Pulse-Doppler (PD) radar systems, the configuration of Pulse Repetition Frequency schedules (PRFs) critically influences detection performance and ambiguity resolution capabilities. Conventional PRFs design algorithms typically focus on either anti-blind-zone or anti-ghost performance individually, lacking an integrated optimization strategy that simultaneously addresses both aspects. This limitation can lead to suboptimal overall performance. To overcome this problem, this paper proposes a novel multi-objective optimization algorithm for PRFs design. This algorithm holistically considers both anti-blind-zone and anti-ghost performances metrics. First, a multi-objective optimization model is established with dual objectives, i.e., minimizing the blind-zone ratio in the range-velocity domain and maximizing the ambiguity resolution margin. Subsequently, the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is employed to solve this optimization problem and obtain the Pareto optimal solution set. Finally, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) combined with Entropy Weight theory is applied for multi-attribute decision-making on the Pareto set to determine the optimal PRFs. Simulation results demonstrate that, compared to existing algorithms, the PRFs designed by the proposed algorithm achieves superior comprehensive performance in both anti-blind-zone and anti-ghost capabilities.