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An effective and efficient heuristic for no-wait flow shop production to minimize total completion time

机译:一种高效的启发式方法,用于无等待的流水车间生产,以最大程度地减少总完成时间

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摘要

No-wait flow shop production has been widely applied in manufacturing. However, minimization of total completion time for no-wait flow shop production is NP-complete. Consequently, achieving good effectiveness and efficiency is a challenge in no-wait flow shop scheduling, where effectiveness means the deviation from optimal solutions and efficiency means the computational complexity or computation time. We propose a current and future idle time (CFI) constructive heuristic for no-wait flow shop scheduling to minimize total completion time. To improve effectiveness, we take current idle times and future idle times into consideration and use the insertion and neighborhood exchanging techniques. To improve efficiency, we introduce an objective increment method and determine the number of iterations to reduce the computation time. Compared with three recently developed heuristics, our CFI heuristic can achieve greater effectiveness in less computation time based on Taillard's benchmarks and 600 randomly generated instances. Moreover, using our CFI heuristic for operating room (OR) scheduling, we decrease the average patient flow times by 11.2% over historical ones in University of Kentucky Health Care (UKHC).
机译:无等待流水车间生产已广泛应用于制造业。但是,使无等待流水车间生产的总完成时间最小化是NP-complete。因此,在没有等待的流水车间调度中,实现良好的效率和效率是一个挑战,其中效率意味着偏离最佳解决方案,效率意味着计算复杂度或计算时间。我们为无等待流水车间调度提出了当前和未来的空闲时间(CFI)构造启发式方法,以最大程度地减少总完成时间。为了提高效率,我们考虑了当前的空闲时间和将来的空闲时间,并使用了插入和邻域交换技术。为了提高效率,我们引入了一种客观的增量方法,并确定迭代次数以减少计算时间。与最近开发的三种启发式算法相比,基于Taillard的基准测试和600个随机生成的实例,我们的CFI启发式算法可以在更短的计算时间内实现更高的有效性。此外,使用我们的CFI启发式手术室(OR)计划,与肯塔基大学医疗保健(UKHC)的历史病人相比,我们的平均病人流动时间减少了11.2%。

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