针对汽车装配线的物料调度问题，以装配线不缺货为约束，构建多设备联合配送的准时化物料供应模型.开展问题域的描述，以优化规划期内的线边库存水平为目标，构建数学规划模型.基于标准教-学算法（TLBO）的框架，提出求解这一复杂组合优化问题的混合教-学算法（HTLBO）.根据问题的特点，设计特定的编码与解码方法，确定各个设备的配送任务及排序.通过融合交换、反转和插入变异算子，构建局部搜索流程，以强化算法的全局开发能力.结合问题的性质，提出基于束搜索技术的剪枝方法，以强化算法的深度寻优能力.开展仿真实验，测试结果验证了该调度算法的可行性和有效性.Abstract: A just-in-time part distribution model with multiple transportation devices was analyzed under consideration of no stock-outs constraints in order to solve the part-supply scheduling problem of the automobile assembly line. The problem domain was described and a mathematical programming model was developed to minimize the line-side inventory levels in the planning horizon. A hybrid teaching-learning-based optimization (HTLBO) approach was established for this complicated combinatorial optimization problem according to the framework of the standard teaching-learning-based optimization (TLBO). A specified encoding and decoding method was proposed to assign and sequence the distribution tasks on each device according to the nature of the proposed scheduling problem. A local search procedure was presented to enhance the exploration ability of the algorithm by incorporating with swap, reversion and insertion operators. A beam-search-based pruning method was proposed by using domain properties in order to enhance the algorithm's exploiting capability. Experiments were conducted. The simulation results validated the feasibility and effectiveness of the proposed scheduling algorithm.