基于混合脉动模型的大规模装配线资源高效调度决策方法

Mixture Pulsation Model-Based Decision-Making for Resource-Efficient Scheduling in Large-Scale Assembly Lines

IEEE Transactions on Cybernetics · 2026
被引 0
ABS 3

中文导读

针对大规模装配线资源分配低效、工作站协调困难及拥堵问题,提出基于混合脉动模型的调度决策方法,通过定量脉动节拍一致性、时空约束任务分配及双层调度-协作架构,显著降低综合调度成本,适用于飞机制造等场景。

Abstract

Large-scale assembly production suffers from inefficient resource allocation, difficulties in coordinating interests across workstations, and severe congestion issues due to massive scale, complex tasks, and fluctuating constraints. To address these challenges, this study proposes a resource-efficient scheduling decision-making method based on a mixture pulsation model (DMMPM). The main contributions are as follows: 1) quantitative criteria for pulsation rhythm (takt-time) consistency in assembly production are defined, and a mixture equilibrium model for multiworkstation collaborative scheduling is developed, to integrate production rhythm alignment with workforce optimization within a coalition-driven profit maximization framework; 2) a spatiotemporally constrained task-allocation method driven by theoretical allocation batches is designed, balancing interstation resource demand conflicts and production rhythm synchronization requirements; and 3) a bi-level "scheduling-collaboration" architecture is proposed, where scheduling agents generate workstation-level strategies and collaboration agents coordinate cross-workstation coalition strategies through profit distribution, thereby enabling the efficient integration of decentralized decision-making and global optimization. The mathematical model is validated using ILOG CPLEX. Compared with conventional approaches, DMMPM significantly reduces the integrated scheduling cost and demonstrates superior decision-making capability and improved control of pulsation rhythm in large-scale aircraft manufacturing scenarios.

生产调度装配线资源分配协同决策大规模制造