In this paper, we are concerned with the problem of scheduling n jobs on m machines. The job processing rate is interdependent and the jobs are non-preemptive. During the last several decades, a number of related models for parallel machine scheduling with interdependent processing rates (PMS-IPR) have appeared in the scheduling literature. Some of these models have been studied independently from one another. The purpose of this paper is to present two general PMS-IPR models that capture the essence of many of these existing PMS-IPR models. Several new complexity results are presented. We discuss improvements on some existing models. Furthermore, for an extension of the two related PMS-IPR models where they include many resource constraint models with controllable processing times, we propose an efficient dynamic programming procedure that solves the problem to optimality.

中文翻译：

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具有相互依赖的处理速率的并行机器调度的统一视图

在本文中，我们关注在 m 台机器上调度 n 个作业的问题。作业处理率是相互依赖的，而且作业是非抢占式的。在过去的几十年中，调度文献中出现了许多具有相互依存处理速率（PMS-IPR）的并行机器调度的相关模型。其中一些模型是相互独立研究的。本文的目的是展示两个通用的 PMS-IPR 模型，它们捕捉了许多现有 PMS-IPR 模型的本质。提出了几个新的复杂性结果。我们讨论了一些现有模型的改进。此外，对于两个相关的 PMS-IPR 模型的扩展，其中包括许多具有可控处理时间的资源约束模型，