Machine breakdowns can lead to scheduling disruptions, causing production stagnation, order delivery delays, and other cascading issues that severely impact the operational efficiency of manufacturing systems. This paper proposes an efficient dynamic scheduling strategy to enhance scheduling stability and production efficiency. First, the strategy introduces a Latin hypercube-based initialization mechanism. This enhances solution diversity and accelerates convergence. Secondly, the paper establish a failure-driven dynamic response strategy by incorporating strong perturbation operations, aiming to achieve rapid and effective rescheduling in response to disruption events. Finally, the paper introduces a greedy ascending order encoding rule to dynamically adjust operation priorities, thereby enhancing the robustness of the scheduling scheme. Experimental results demonstrate that the proposed strategy outperforms particle swarm optimization and grey wolf optimizer in both efficiency and stability.