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.
Gao et al. (Thu,) studied this question.