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Global Cyclic Cumulative Constraint

机译:全局循环累积约束

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摘要

This paper proposes a global cumulative constraint for cyclic scheduling problems. In cyclic scheduling a project graph is periodically re-executed on a set of limited capacity resources. The objective is to find an assignment of start times to activities such that the feasible repetition period A is minimized. Cyclic scheduling is an effective method to maximally exploit available resources by partially overlapping schedule repetitions. In our previous work [4], we have proposed a modular precedence constraint along with its filtering algorithm. The approach was based on the hypothesis that the end times of all activities should be assigned within the period: this allows the use of traditional resource constraints, but may introduce resource inefficiency. The adverse effects are particularly relevant for long activity durations and high resource availability. By relaxing this restriction, the problem becomes much more complicated and specific resource constrained filtering algorithms should be devised. Here, we introduce a global cumulative constraint based on modular arithmetic, that does not require the end times to be within the period. We show the advantages obtained for specific scenarios in terms of solution quality with respect to our previous approach, that was already superior with respect to state of the art techniques.
机译:本文提出了一种针对循环调度问题的全局累积约束。在循环调度中,将在一组有限容量的资源上定期重新执行项目图。目的是找到对活动的开始时间的分配,以使可行的重复周期A最小。循环调度是通过部分重叠调度重复来最大程度地利用可用资源的有效方法。在我们以前的工作[4]中,我们提出了一个模块化优先约束及其过滤算法。该方法基于以下假设:所有活动的结束时间都应在该时间段内分配:这允许使用传统的资源约束,但可能导致资源效率低下。不利影响与长时间的活动持续时间和高资源可用性特别相关。通过放宽此限制,问题变得更加复杂,应设计特定的资源受限过滤算法。在这里,我们引入基于模块化算法的全局累积约束,它不需要结束时间在周期内。我们展示了在特定方案中相对于我们以前的方法在解决方案质量方面所获得的优势,相对于最新技术而言,这些优势已经优越。

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