On the Distribution of Activity Time in PERT

Golenko‐Ginzburg, Dimitri

doi:10.2307/2583772

Cited by 8 publications

(12 citation statements)

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“…The lower limit (LL) is set equal to 0.75 times the baseline value. The difference between the baseline value and the LL is assumed to be 1/3 the difference between the upper limit (UL) and LL (Golenko‐Ginzburg, ). Standard error is calculated from the following equation: (UL − LL) / 2 × 1.96.…”

Section: Methodsmentioning

confidence: 99%

“…The LL was set equal to remission rate on RT. Baseline value was calculated as follows: x = LL + 1/3 (UL − LL) (Golenko‐Ginzburg, ).…”

Section: Methodsmentioning

confidence: 99%

“…The LL was set equal to 0.75 times the baseline value. The difference between the baseline value and the LL was assumed to be 1/3 the difference between the UL and LL (Golenko‐Ginzburg, ). Then, we retrieved slope parameters and solving equations: mean = /( a + b ); SD = √[( ab ) / ( a + b )2( a + b + 1)] (Shaw and Zachr, ).…”

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Benefit of slow titration of paroxetine to treat depression in the elderly

Olgiati

Bajo

Serretti

2014

Human Psychopharmacology

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Section: Methodsmentioning

confidence: 99%

“…The LL was set equal to remission rate on RT. Baseline value was calculated as follows: x = LL + 1/3 (UL − LL) (Golenko‐Ginzburg, ).…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Benefit of slow titration of paroxetine to treat depression in the elderly

Olgiati

Bajo

Serretti

2014

Human Psychopharmacology

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“…It also considers the task durations as random variables and the beta distribution as the appropriate one in order to model them. Other authors that presented research contributions on PERT are: Grubbs [17], MacCrimmon and Rayvec [28], Hartley and Northam [19], Moder and Rodgers [30], Parks and Ramsing [37], Ringer [39], Kotiah and Wallace [23], Britney [3], Sasieni [41], Farrum and Stanton [12], Gallanger [13], Golenko-Ginsburg [15] and [16], Moitra [32], Keefer and Verdini [21], Wayne and Cottrell [45], Lu [26].…”

Section: Literature Reviewmentioning

confidence: 99%

“…The authors equate the relations (14), (15) with the relations (1), (2) respectively. Here, the authors consider the shape parameters q and r as fuzzy numbers.…”

Section: Estimation Of Parameters Of the Generalized Beta Distributiomentioning

confidence: 99%

Approaching activity duration in PERT by means of fuzzy sets theory and statistics

Chrysafis

Papadopoulos

2014

Journal of Intelligent &Amp; Fuzzy Systems

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Taking into account the intrinsic drawbacks of both classic and fuzzy PERT, the authors present a new approach in an attempt to deal with them. The tools for this approach are fuzzy statistics and fuzzy probabilities. A necessary condition for this approach is the existence of statistical data for the project activity duration. The final findings are the fuzzy activity times (earliest/latest start -earliest/latest finish), the fuzzy float, the Criticality Degree both for each activity and for each path, a fuzzy probability for the activity duration to be in a certain time interval and a fuzzy probability for the project completion time to be in certain time interval. A numerical example is provided for thorough comprehension.

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Quantifying Schedule Delay Risk in Construction Projects: A Data-Driven Approach with BIM and Probabilistic Reliability Analysis

Zhang,

Wang

2023

Advances in Civil Engineering

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Progress management is an important scheme of construction management. In practical affairs, many unknown factors may lead to potential project delays and make the schedule risky. To address this issue, this paper proposes a data-driven construction progress evaluation method that employs a probabilistic reliability analysis with BIM to effectively quantify the risk of schedule delay. By identifying critical tasks and probable failure conditions in uncertain environments, this method enables project managers to take proactive measures to keep their projects on schedule. Through our case study, we have demonstrated that the proposed method is highly effective in dynamically evaluating the project progress with both accuracy and efficiency. Besides, this system offers a more efficient way for managers to gather information, evaluate progress, and identify critical tasks, and provides project managers with a data-driven understanding of the risks and uncertainties related to project schedules, enabling them to take proactive measures to minimize the potential delays and ensure successful project delivery.

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On the Distribution of Activity Time in PERT

Cited by 8 publications

References 0 publications

Benefit of slow titration of paroxetine to treat depression in the elderly

Benefit of slow titration of paroxetine to treat depression in the elderly

Approaching activity duration in PERT by means of fuzzy sets theory and statistics

Quantifying Schedule Delay Risk in Construction Projects: A Data-Driven Approach with BIM and Probabilistic Reliability Analysis

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