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Integrating Risk into Project Control Using Bayesian Networks
International Journal of Information Technology & Decision Making ( IF 4.9 ) Pub Date : 2020-07-13 , DOI: 10.1142/s0219622020500315
Erhan Pişirir 1, 2 , Yasemin Sü 2 , Barbaros Yet 2
Affiliation  

Projects are, by definition, risky and uncertain ventures. Therefore, the performance and risk of major projects should be carefully controlled in order to increase their probability of success. Quantitative project control techniques assist project managers in detecting problems, thus responding to them early on, by comparing the baseline plan with the project progress. However, project risk and uncertainty are rarely considered by these techniques. This paper proposes a project control framework that integrates the project uncertainty and associated risk factors into project control. Our framework is based on earned value management (EVM), which is an effective and widely used quantitative project control technique. The framework uses hybrid Bayesian Networks (BNs) to enhance EVM with the ability to compute the uncertainty associated with its parameters and risk factors. The framework can be applied to projects from different domains, and we illustrate its use with a simple example and a case study of a construction project.

中文翻译:

使用贝叶斯网络将风险整合到项目控制中

根据定义,项目是风险和不确定的企业。因此,应谨慎控制重大项目的绩效和风险,以增加其成功的可能性。定量项目控制技术通过将基线计划与项目进度进行比较,帮助项目经理发现问题,从而及早做出响应。然而,这些技术很少考虑项目风险和不确定性。本文提出了一个项目控制框架,将项目不确定性和相关风险因素整合到项目控制中。我们的框架基于挣值管理 (EVM),这是一种有效且广泛使用的量化项目控制技术。该框架使用混合贝叶斯网络 (BN) 来增强 EVM,使其能够计算与其参数和风险因素相关的不确定性。该框架可以应用于不同领域的项目,我们通过一个简单的例子和​​一个建设项目的案例研究来说明它的使用。
更新日期:2020-07-13
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