论文标题
在线算法安排成比例的弹性流店批处理机
Online Algorithms to Schedule a Proportionate Flexible Flow Shop of Batching Machines
论文作者
论文摘要
本文是第一个考虑在线算法安排批处理机(PFFB)的柔性流动商店的算法。调度模型是由个性化药物的制造过程激励的,该过程在现代医学中用于治疗一些严重疾病。我们提供两种不同的在线算法,证明了离线问题的下限,以计算其竞争比率。第一种算法是一种易于实施的本地日程安排。对于具有任意阶段数量和几个自然计划目标的PFFB的PFFB,它是2竞争性的。我们还表明,对于总/平均流动时间,不存在具有更好竞争比率的确定性算法。对于具有两个阶段的特殊情况以及MakePAN或总完成时间目标,我们描述了一种改进的算法,该算法达到了最佳的竞争比率$φ= \ frac {1+ \ sqrt {5}}} {2} {2} {2} $,黄金比率。我们所有的结果也适用于批处理机(PFB)的比例(不易燃料)流店,这也是研究在线算法的第一篇论文。
This paper is the first to consider online algorithms to schedule a proportionate flexible flow shop of batching machines (PFFB). The scheduling model is motivated by manufacturing processes of individualized medicaments, which are used in modern medicine to treat some serious illnesses. We provide two different online algorithms, proving also lower bounds for the offline problem to compute their competitive ratios. The first algorithm is an easy-to-implement, general local scheduling heuristic. It is 2-competitive for PFFBs with an arbitrary number of stages and for several natural scheduling objectives. We also show that for total/average flow time, no deterministic algorithm with better competitive ratio exists. For the special case with two stages and the makespan or total completion time objective, we describe an improved algorithm that achieves the best possible competitive ratio $φ=\frac{1+\sqrt{5}}{2}$, the golden ratio. All our results also hold for proportionate (non-flexible) flow shops of batching machines (PFB) for which this is also the first paper to study online algorithms.