为求解以最大完工时间、平均延迟时间、瓶颈机器加工负载率为目标的柔性生产调度优化问题，针对机器分配与任务排序的决策复杂度与约束特征，提出了以二维染色体编码机器分配、启发式规则评估任务排序优先级的混合决策机制调度算法，以增强对决策优化的适应水平。为了进一步改善所提调度方法的性能，制定了以等待调度任务所需加工时长分布为依据的自适应规则策略，实现决策对调度场景的动态适应性，提升全局优化的综合优势水平。实验结果表明：该方法提高了调度问题求解的寻优效率，提供更加占据主导地位的非支配解集。

To optimize flexible production scheduling with the objectives of the longest makespan, mean tardiness, and bottleneck machine processing load rate, a hybrid decision-making mechanism scheduling algorithm was proposed based on the decision complexity and constraint characteristics of machine assignment and task sequencing. The algorithm adopted a two-dimensional chromosome to encode machine assignment and a heuristic rule to evaluate task sequencing priority, enhancing the adaptability of the method to decision-making optimization. In order to further improve the performance of the proposed scheduling method, an adaptive rule strategy was designed based on the distribution of processing time required for waiting scheduling tasks to achieve dynamic adaptability of the decision-making to scheduling scenarios, thereby improving the comprehensive advantage level of global optimization. Experimental tests show that the proposed method helps to improve the optimization efficiency of scheduling and provides non-dominated solution sets occupying higher dominant positions.