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Evaluating the planning efficiency for repetitive construction projects using Monte Carlo simulation technique
Ahmed M Ebid1, Taher Ammar2, Ibrahim Mahdi3
1Department of Structural Engineering and Construction Management, Future University in Egypt, New Cairo, Egypt. ahmed.abdelkhaleq@fue.edu.eg.
Scientific Reports
|July 28, 2025
Summary
This study introduces a Monte Carlo simulation framework for efficient highway construction planning. The data-driven approach significantly improves project scheduling and resource management, outperforming traditional methods.
Area of Science:
- Construction Management
- Operations Research
- Civil Engineering
Background:
- Efficient planning and scheduling are vital for repetitive construction projects, especially highway infrastructure.
- Traditional methods struggle with uncertainties and resource fluctuations in large-scale projects.
Purpose of the Study:
- To develop and validate a Monte Carlo simulation-based framework for enhancing repetitive construction project planning.
- To systematically model activity prioritization, resource allocation, and schedule optimization.
Main Methods:
- Utilized Monte Carlo simulation to model uncertainties in project parameters.
- Analyzed eighteen hypothetical project cases under varying conditions.
- Validated the framework with three real-world highway projects in Egypt.
Main Results:
- Demonstrated substantial improvements in project duration and resource utilization efficiency compared to conventional methods.
- Achieved efficiency gains of up to 80% in real-world highway projects.
- The framework effectively mitigates uncertainties and optimizes project outcomes.
Conclusions:
- The proposed Monte Carlo simulation framework offers a data-driven, adaptable solution for repetitive construction planning.
- Provides a robust tool for planners to improve efficiency and mitigate risks.
- Confirms practical applicability and significant benefits for highway infrastructure projects.
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