The goal of this paper is to present concepts and methods that allow us to account for real-time data in online scheduling without embedding a dynamic model. First, we discuss the key role played by the progress status of a batch, the key state in scheduling. Specifically, we show how fractional changes in the progress status necessitate the re-calculation, using real-time data, of parameters used in scheduling models (which have always been thought to be constants). Second, we present algorithms for the calculation of the progress status and the above parameters. Third, we present a state-space resource task network (RTN) formulation employing parameters calculated in real-time and show why, in this context, it should account for delays of batches under execution as optimization decisions. Finally, we show how the proposed methods lead to tractable optimization problems and can be used to address problems that cannot be solved using existing scheduling approaches.

本文的目的是提出一些概念和方法，这些概念和方法使我们能够在不嵌入动态模型的情况下在联机调度中考虑实时数据。首先，我们讨论批处理进度状态，调度中的关键状态所起的关键作用。具体来说，我们展示了进度状态的微小变化如何需要使用实时数据重新计算调度模型中使用的参数（一直被认为是常量）。其次，我们介绍了用于计算进度状态和上述参数的算法。第三，我们提出了一种使用实时计算的参数的状态空间资源任务网络（RTN）公式，并说明了为什么在这种情况下它应该考虑执行中的批次延迟作为优化决策。最后，