基于关键路径动态排序方法的多舰载机保障工作流调度

A Critical Path-driven Scheduling Algorithm for Multi-Carrier Aircraft Support Workflows

  • 摘要:目的】舰载机舰面保障作业调度是航母作战保障体系的重要环节。现有研究多采用柔性作业车间调度模型,难以充分描述保障任务中作业顺序可调、多工序并行以及资源—阵位耦合等特性。为此,提出一种基于关键路径动态排序的工作流保障调度方法。【方法】将多机协同保障流程建模为具有时空约束的工作流调度问题,构建能够描述任务逻辑依赖、并行关系和资源占用关系的数学模型;进一步设计关键路径动态排序算法,通过动态识别关键路径、更新边权重并调整任务优先级,结合资源—阵位匹配策略,实现任务执行顺序与资源分配方案的协同优化。【结果】实验结果表明,所提算法相比传统异构最早完成时间算法可将保障完成时间缩短5.99%。【结论】该方法提升了舰载机舰面保障任务灵活性与并行性的建模能力,为复杂约束下的保障作业调度提供了有效求解方法。

     

    Abstract: Objectives Carrier-based aircraft deck support operation scheduling is an important part of the aircraft carrier combat support system. Existing studies mostly adopt flexible job shop scheduling models, which makes it difficult to fully describe such characteristics as adjustable operation sequences, parallel execution of multiple operations, and coupled resource-station constraints in support tasks. To address this issue, a workflow support scheduling method based on dynamic critical-path ranking is proposed. Methods The multi-aircraft collaborative support process is modeled as a workflow scheduling problem with spatiotemporal constraints, and a mathematical model is constructed to describe task logical dependencies, parallel relationships, and resource occupation relationships. Furthermore, a dynamic critical-path ranking algorithm is designed, in which the critical path is dynamically identified, edge weights are updated, and task priorities are adjusted. Combined with a resource-station matching strategy, the proposed algorithm realizes the coordinated optimization of task execution sequences and resource allocation schemes. Results Experimental results show that, compared with the traditional heterogeneous earliest-finish-time algorithm, the proposed algorithm reduces the support completion time by 5.99%. Conclusions The proposed method improves the modeling capability for task flexibility and parallelism in carrier-based aircraft deck support operations, and provides an effective solution method for support operation scheduling under complex constraints.

     

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