Improving the Performance of Queueing Systems through Cross-Training

通过交叉训练提高排队系统的性能

基本信息

批准号：
0000135
负责人：
Sigrun Andradottir
金额：
$ 31.79万
依托单位：
Georgia Tech Research Corporation
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2000
资助国家：
美国
起止时间：
2000-06-15 至 2005-05-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=0000135&HistoricalAwards=false
关键词：
Improving Performance Queueing Systems through

项目摘要

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.

这笔赠款为研究如何分配工人执行任务提供了资金，假设工人可以接受交叉培训以能够执行各种任务。目标是制定易于实施、稳健和动态的工作分配政策，以实现吞吐量、停留时间和在制品等绩效指标的改进。该研究还将寻求确定特定工作分配策略将带来最大效益的条件，量化由此产生的绩效改进的幅度，确定这些策略对绩效改进影响最大的方面，并调查以下因素的敏感性：结果与所做出的具体（建模和分析）假设有关。为了实现该项目的目标，组织将被建模为排队系统，并使用多种方法进行分析（即马尔可夫链分析、马尔可夫决策过程、随机比较、流体松弛和模拟）。如果成功，该结果研究预计将包括关于如何使用交叉培训和动态工作分配策略来提高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见解，管理者可以利用这些见解对组织的劳动力利用方式实施简单的改变，从而可能提高绩效。