Improving the Performance of Queueing Systems through Cross-Training

这笔赠款为一项关于如何分配工人执行任务的研究提供了资金，假设工人可以接受交叉培训，以便能够执行各种任务。目标是开发易于实现的、健壮的、动态的工作分配策略，以实现吞吐量、逗留时间和在制品等性能指标的改进。这项研究还将力求确定在哪些情况下特定的工作分配战略将是最有益的，量化由此产生的业绩改进的程度，确定这些战略中对改进业绩影响最大的方面，并调查结果对具体(建模和分析)假设的敏感性。为了实现这个项目的目标，组织将被建模为排队系统，并使用多种方法(即马尔科夫链分析、马尔可夫决策过程、随机比较、流体松弛和模拟)进行分析。如果成功，本研究的结果将包括如何使用交叉培训和动态工作分配策略来改进组织绩效以及通过实施这些策略可以获得多少收益的详细指南。这项研究还有望提供定性的见解，经理们可以利用这些见解来实施组织如何利用劳动力的简单变化，这些变化可能会带来更好的绩效。

This grant provides funding for a study of how workers should be assigned to tasks, assuming that the workers can be cross-trained to capably perform a variety of tasks. The goal is to develop easily implementable, robust, and dynamic work assignment policies that achieve improvements in performance measures such as throughput, sojourn time, and work in process. The research will also seek to identify the conditions under which particular work assignment strategies will be of greatest benefit, quantify the magnitude of the resulting performance improvements, determine the aspects of these strategies that have the greatest impact towards improved performance, and investigate the sensitivity of the results to the specific (modeling andanalysis) assumptions made. In order to achieve the goals of this project, organizations will be modeled as queueing systems and analyzed using several methodologies (i.e., Markov chain analysis, Markov decision processes, stochastic comparisons, fluid relaxation, and simulation).If successful, the results of this research are expected to include detailed guidelines for how cross-training and dynamic work assignment strategies can be used to improve an organization's performance and for how much benefit can be obtained by implementing these strategies. This research is also expected to to provide qualitative insights that managers can use to implement simple changes in how their organization's workforce is utilized that are likely to yield improved performance.