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Minimizing the expected makespan of a project with stochastic activity durations under resource constraints

机译:在资源紧张的情况下,将活动持续时间随机的项目的预期工期最小化

摘要

The resource-constrained project scheduling problem (RCPSP) has been widely studied. A fundamental assumption of the basic type of RCPSP is that activity durations are deterministic (i.e., they are known in advance). In reality, however, this is almost never the case. In this article we illustrate why it is important to incorporate activity duration uncertainty, and develop an exact procedure to optimally solve the stochastic resource-constrained scheduling problem (SRCPSP). A computational experiment shows that our approach works best when solving small-to medium-sized problem instances where activity durations have a moderate-to-high level of variability. For this setting, our model outperforms the existing state-of-the-art. In addition, we use our model to assess the optimality gap of existing heuristic approaches, and investigate the impact of making scheduling decisions also during the execution of an activity rather than only at the end of an activity.
机译:资源受限的项目调度问题(RCPSP)已被广泛研究。 RCPSP基本类型的基本假设是活动持续时间是确定性的(即预先知道)。但是,实际上,几乎从来没有这样。在本文中,我们说明了为什么合并活动持续时间不确定性很重要,并开发出精确的过程来最佳地解决随机资源受限的调度问题(SRCPSP)。一项计算实验表明,当活动持续时间具有中等到高度可变性的中小型问题实例时,我们的方法最有效。在此设置下,我们的模型优于现有的最新技术。此外,我们使用模型来评估现有启发式方法的最佳差距,并在活动执行期间(而不是仅在活动结束时)调查制定计划决策的影响。

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    Creemers Stefan;

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