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Scheduling of deteriorating jobs with release dates to minimize the maximum lateness

机译:安排恶化的工作并安排发布日期,以最大程度地减少最大延迟

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In this paper, we consider the problem of scheduling n deteriorating jobs with release dates on a single (batching) machine. Each job's processing time is a simple linear function of its starting time. The objective is to minimize the maximum lateness. When the machine can process only one job at a time, we first show that the problem is NP-hard even if there are only two distinct release dates. Then we present a 2-approximation algorithm for the case where all jobs have negative due dates. Furthermore, we prove that the earliest due date (EDD) rule provides an optimal solution to the case where all jobs have agreeable release dates, due dates and deteriorating rates, and that the EDD rule gives the worst order for the general case, respectively. When the machine can process up to b(b = ∞) jobs simultaneously as a batch, i.e., the unbounded parallel-batch scheduling model, we show that the problem is NP-hard and present one property of the optimal schedule for the case where all jobs have agreeable release dates and due dates.
机译:在本文中,我们考虑在单个(批处理)计算机上安排带有发布日期的n个性能下降的作业的问题。每个作业的处理时间是其开始时间的简单线性函数。目的是最小化最大延迟。当机器一次只能处理一个作业时,我们首先表明问题是NP难题,即使只有两个不同的发布日期。然后,针对所有作业均具有负到期日的情况,我们提出了一种2近似算法。此外,我们证明了最早的到期日(EDD)规则为所有作业具有一致的发布日期,到期日和恶化率的情况提供了最佳解决方案,并且EDD规则分别为一般情况提供了最差的排序。当机器可以同时批量处理多达b(b =∞)个作业时,即无边界并行批处理调度模型,我们证明问题是NP难的,并且针对以下情况提供了最优调度的一个属性:所有工作都有合适的发布日期和截止日期。

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