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Towards Finding Robust Execution Strategies for RCPSP/max with Durational Uncertainty

机译:寻求具有持续不确定性的RCPSP / max的鲁棒执行策略

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Resource Constrained Project Scheduling Problems with minimum and maximum time lags (RCPSP/max) have been studied extensively in the literature. However, the more realistic RCPSP/max problems - ones where durations of activities are not known with certainty - have received scant interest and hence are the main focus of the paper. Towards addressing the significant computational complexity involved in tackling RCPSP/max with durational uncertainty, we employ a local search mechanism to generate robust schedules. In this regard, we make two key contributions: (a) Introducing and studying the key properties of a new decision rule to specify start times of activities with respect to dynamic realizations of the duration uncertainty; and (b) Deriving the fitness function that is used to guide the local search towards robust schedules. Experimental results show that the performance of local search is improved with the new fitness evaluation over the best known existing approach.
机译:具有最小和最大时滞(RCPSP / max)的资源受限项目计划问题已在文献中进行了广泛研究。但是,更为现实的RCPSP / max问题(不确定活动的持续时间的问题)兴趣不大,因此是本文的重点。为了解决在解决具有持续时间不确定性的RCPSP / max时涉及的显着计算复杂性问题,我们采用了局部搜索机制来生成可靠的计划。在这方面,我们做出了两个关键贡献:(a)介绍和研究新决策规则的关键属性,以针对持续时间不确定性的动态实现指定活动的开始时间; (b)推导适应度函数,该函数用于指导本地搜索朝着稳健的时间表发展。实验结果表明,通过新的适应性评估,可以比最知名的现有方法提高局部搜索的性能。

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