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Practical crash duration estimation for project schedule activities

机译:项目进度活动的实用崩溃持续时间估计

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The increasing demand in project acceleration in the construction industry has led to the development of a practical crash duration estimation model for activities. This study aims to develop a general model of crash duration (CD) estimation for project activities based on crash duration coefficient (CDC) and normal duration (ND). This study uses questionnaires to explore the judgment of 425 respondents regarding CD data. Three rules of thumb are employed: developing the 45 CDC’s distribution for each project activity; generalizing the most likely of the distributions; and developing a CD estimation model. The combination of the bootstrapping and Monte Carlo simulation techniques are used to generate population distributions of the sampling. The practical CD estimation model of (0.55?±?0.1) ND is proposed to project an acceleration problem. The accuracy of the CD estimation is determined from the general CDC distribution value of 55% with a tolerance of approximately ±20% (0.1 ND/0.55 ND?≈?±20%) is as a stochastic value. The CDC can be stated as a qualitative expression of a specific property of an activity in predicting the CD, and it plays an important role for CD accuracy and can identify risk-taking preferences. Using the risk-taking category in an interval scale is more logical for the qualitative assessment of the preferences of decision makers. CDC distribution models can provide additional information on certain conditions regarding the current CD practice, in which the contractors’ understanding of the distribution pattern could have distinct advantages over other contractors, who only depend on their experience and preferences.
机译:建筑业项目加速需求日益增长导致开发活动的实用碰撞持续时间估算模型。本研究旨在基于碰撞持续时间系数(CDC)和正常持续时间(ND)开发项目活动的碰撞持续时间(CD)估计的一般模型。本研究使用问卷来探索425名受访者关于CD数据的判断。采用三项经验法则:为每个项目活动制定45个CDC的分发;概括最有可能的分布;并开发CD估计模型。自举和蒙特卡罗仿真技术的组合用于产生采样的人口分布。 (0.55?±0.1)ND的实际CD估计模型被提出投影加速问题。 CD估计的准确性从一般CDC分布值确定55%,公差约为±20%(0.1nd / 0.55 nd?≈α±20%)是随机值。 CDC可以表示为预测CD中活性的特异性性质的定性表达,并且它对CD精度发挥着重要作用,可以识别风险偏好。以间隔规模使用风险采取的类别对于决策者的偏好进行定性评估更为逻辑。 CDC分配模型可以提供有关当前CD实践的某些条件的额外信息,其中承包商对分销模式的理解可能与其他承包商具有不同的优势,该承包商只取决于他们的经验和偏好。

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