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Forecasting the Project Duration Average and Standard Deviation from Deterministic Schedule Information

Ballesteros-Pérez, P; Cerezo-Narváez, A; Otero-Mateo, M; Pastor-Fernández, A; Zhang, J; Vanhoucke, M; (2020) Forecasting the Project Duration Average and Standard Deviation from Deterministic Schedule Information. Applied Sciences , 10 (2) , Article 654. 10.3390/app10020654. Green open access

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Abstract

Most construction managers use deterministic scheduling techniques to plan construction projects and estimate their duration. However, deterministic techniques are known to underestimate the project duration. Alternative methods, such as Stochastic Network Analysis, have rarely been adopted in practical contexts as they are commonly computer-intensive, require extensive historical information, have limited contextual/local validity and/or require skills most practitioners have not been trained for. In this paper, we propose some mathematical expressions to approximate the average and the standard deviation of a project duration from basic deterministic schedule information. The expressions’ performance is successfully tested in a 4100-network dataset with varied activity durations and activity durations variability. Calculations are quite straightforward and can be implemented manually. Furthermore, unlike the Project Evaluation and Review Technique (PERT), they allow drawing inferences about the probability of project duration in the presence of several critical and subcritical paths with minimal additional calculation.

Type: Article
Title: Forecasting the Project Duration Average and Standard Deviation from Deterministic Schedule Information
Open access status: An open access version is available from UCL Discovery
DOI: 10.3390/app10020654
Publisher version: https://doi.org/10.3390/app10020654
Language: English
Additional information: This is an open access article distributed under the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Keywords: project duration; scheduling; merge event bias; construction; PERT
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > UCL School of Management
URI: https://discovery.ucl.ac.uk/id/eprint/10102159
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