Pulsating production lines have become a pivotal solution in aircraft assembly systems due to their operational efficiency and advanced synchronization mechanisms‌. However, existing methodologies for designing workstation layouts in component assembly fail to comprehensively address critical requirements including assembly rhythm synchronization, precision constraints, and capacity balancing in pulsating production environments. This study systematically investigates the design framework and operational principles of pulsating production lines for aircraft component assembly, proposing a hybrid optimization methodology that integrates three algorithmic approaches, including Cuckoo Search (CS) for workstation quantity optimization, NSGA-II for assembly sequence optimization and Particle Swarm Optimization (PSO) for resource allocation. The multi-objective model simultaneously minimizes the Smoothing Index (SI) and total resource consumption while adhering to constraints such as assembly time thresholds and sequence dependencies. Validation through standardized case studies confirms the model's superior performance in balancing production stability and resource efficiency. A practical implementation involving rear fuselage component assembly demonstrates the model's capability to derive optimal configurations for workstation quantity, assembly sequence, and resource parameters. This research provides theoretical and operational guidance for enhancing the precision and throughput of modern aircraft assembly systems.