Simulation-Based Approximation of the Gain from Applying Overlapping Activities
Publication: Journal of Construction Engineering and Management
Volume 150, Issue 4
Abstract
Schedule management is essential in construction projects to ensure successful completion. However, the dynamic nature of the construction industry introduces variability, leading to uncertainty and challenges in schedule implementation. This paper explores the use of schedule acceleration through overlapping activities as a solution to mitigate the impact of variability on project timelines. Risks associated with overlapping activities can lead to waste and offset anticipated schedule gains. To challenge the assumption that the schedule gain from activity overlapping is directly proportional to the amount of overlapping, a simulation model is developed and implemented in MATLAB where activities are modeled as beta-distributions. The model gradually increases the overlap percentage and evaluates the mean best-case, overall mean, and mean worst-case durations. An isolated overlap consisting of two activities is used to demonstrate the effect of overlapping. With a ratio between durations, it was found that, when using a 90% overlap, the loss in effect varied from 3.2% to 57.5% with an overall mean loss of 34.2%. These results emphasize that even in the most optimistic combination of distributions, the most likely duration still exceeds initial expectations, indicating the influence of variability on the schedule. Thus, the findings highlight the necessity of project managers to consider the impact of variability on overlapping activities, ensuring a more accurate schedule estimation. The study offers practical recommendations for project managers, including a diagram that advocates applying adjustment coefficients based on the degree of overlap and the ratio between the activity’s durations. The diagram can be adopted in future scheduling to adjust durations when applying overlapping to minimize the risk of schedule delays.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This research is partially supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) Alliance Grant ALLRP 549210-19.
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© 2024 American Society of Civil Engineers.
History
Received: Jun 19, 2023
Accepted: Nov 17, 2023
Published online: Jan 30, 2024
Published in print: Apr 1, 2024
Discussion open until: Jun 30, 2024
ASCE Technical Topics:
- Approximation methods
- Business management
- Construction engineering
- Construction industry
- Construction management
- Continuum mechanics
- Dynamics (solid mechanics)
- Engineering fundamentals
- Engineering mechanics
- Management methods
- Managers
- Methodology (by type)
- Mitigation and remediation
- Models (by type)
- Motion (dynamics)
- Personnel (type)
- Personnel management
- Practice and Profession
- Scheduling
- Simulation models
- Solid mechanics
- Uncertainty principles
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