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Anticipation and flexibility in dynamic scheduling

机译：动态调度的预期和灵活性

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Many real-world optimization problems change over time and require frequent re-optimization. We suggest that in such environments, an optimization algorithm should reflect the problem's dynamics and explicitly take into account that changes to the current solution are to be expected. We claim that this can be achieved by having the optimization algorithm search for solutions that are not only good, but also flexible, i.e. easily adjustable if necessary in the case of problem changes. For the example of a job-shop with jobs arriving non-deterministically over time, we demonstrate that avoiding early idle times increases flexibility, and thus that the incorporation of an early idle time penalty as secondary objective into the scheduling algorithm can greatly enhance the overall system performance.
机译：许多现实世界中的优化问题会随着时间而变化，并且需要频繁进行重新优化。我们建议在这样的环境中，优化算法应反映问题的动态，并明确考虑到将要对当前解决方案进行更改。我们声称，这可以通过使优化算法搜索不仅好而且灵活的解决方案来实现，即在问题变化的情况下必要时易于调整。以一个随着时间的推移不确定地到达工作的车间的例子，我们证明了避免提早闲置时间会增加灵活性，因此将提早闲置时间惩罚作为次要目标并入调度算法可以极大地提高整体效率。系统性能。

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