Decentralised scheduling has been recently advocated as a promising alternative to overcome the difficulties of scheduling jobs in today’s complex and uncertain manufacturing scenarios using the traditional (i.e. centralised) approach consisting of developing a global schedule under the assumption that all necessary data are available and known in advance. In the decentralised approach, machines in the shop floor interact among them to negotiate the jobs to be processed according to a weighted combination of indicators that reflect the current shop floor status. While earlier works have shown the potential advantages of this approach as compared to the centralised one, often these studies are too specific to obtain more generalisable conclusions, since they focus on a single illustrative case study with a small number of jobs/machines, and conduct a limited comparison of both approaches. Furthermore, while its ability to capture current shop floor conditions makes decentralised scheduling more adaptative and flexible than its centralised counterpart, its local (myopic) nature results in a low performance under certain conditions. Therefore, another aspect worth of investigation is to study if a combination of both approaches could ideally result in a more efficient hybrid scheduling mechanism for a wider range of scenarios.

中文翻译：

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评估调度决策中的集中化水平：混合方法的作用


最近，分散式调度被提倡为一种很有前途的替代方案，以克服在当今复杂和不确定的制造场景中调度工作的困难，使用传统的（即集中式）方法，该方法包括在假设所有必要的数据都可用并提前知道的情况下制定全球调度。在分散式方法中，车间中的机器在它们之间进行交互，根据反映当前车间状态的指标加权组合协商要处理的工作。虽然早期的工作已经显示了这种方法与集中式方法相比的潜在优势，但这些研究通常过于具体而无法获得更普遍的结论，因为它们侧重于具有少量工作/机器的单个说明性案例研究，并且对两种方法进行了有限的比较。此外，虽然它能够捕捉当前车间条件，使分散式调度比集中式调度更具适应性和灵活性，但其局部（短视）性质导致在某些情况下性能不佳。因此，另一个值得研究的方面是研究这两种方法的结合是否可以理想地为更广泛的场景带来更高效的混合调度机制。