Evaluating the planning efficiency for repetitive construction projects using Monte Carlo simulation technique
Abstract Efficient planning and scheduling are critical for the success of repetitive construction projects, particularly highway infrastructure, which underpins economic growth in developing regions. Traditional scheduling methods often rely heavily on planner experience, limiting their ability to...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-12779-w |
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| author | Ahmed M. Ebid Taher Ammar Ibrahim Mahdi Hosam Hegazy |
| author_facet | Ahmed M. Ebid Taher Ammar Ibrahim Mahdi Hosam Hegazy |
| author_sort | Ahmed M. Ebid |
| collection | DOAJ |
| description | Abstract Efficient planning and scheduling are critical for the success of repetitive construction projects, particularly highway infrastructure, which underpins economic growth in developing regions. Traditional scheduling methods often rely heavily on planner experience, limiting their ability to manage uncertainties and resource fluctuations in large-scale projects. This study proposes a Monte Carlo simulation-based framework to enhance planning efficiency by systematically modeling activity prioritization, resource allocation, and schedule optimization. Eighteen hypothetical project cases were analyzed under varying conditions to capture a wide range of uncertainties. The results demonstrated substantial improvements in project duration and resource utilization efficiency compared to conventional methods. Validation using three real-world highway projects in Egypt confirmed the framework’s practical applicability, achieving efficiency improvements of up to 80%. This research offers a data-driven, adaptable approach to repetitive project planning, providing planners with a robust tool to mitigate uncertainties and optimize project outcomes. |
| format | Article |
| id | doaj-art-08badb83f2b14a1ca9a7dd3a675818fa |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-08badb83f2b14a1ca9a7dd3a675818fa2025-08-20T03:46:07ZengNature PortfolioScientific Reports2045-23222025-07-0115111210.1038/s41598-025-12779-wEvaluating the planning efficiency for repetitive construction projects using Monte Carlo simulation techniqueAhmed M. Ebid0Taher Ammar1Ibrahim Mahdi2Hosam Hegazy3Department of Structural Engineering and Construction Management, Future University in EgyptNile Engineering Consulting Bureau (NECB)Department of Structural Engineering and Construction Management, Future University in EgyptDepartment of Structural Engineering and Construction Management, Future University in EgyptAbstract Efficient planning and scheduling are critical for the success of repetitive construction projects, particularly highway infrastructure, which underpins economic growth in developing regions. Traditional scheduling methods often rely heavily on planner experience, limiting their ability to manage uncertainties and resource fluctuations in large-scale projects. This study proposes a Monte Carlo simulation-based framework to enhance planning efficiency by systematically modeling activity prioritization, resource allocation, and schedule optimization. Eighteen hypothetical project cases were analyzed under varying conditions to capture a wide range of uncertainties. The results demonstrated substantial improvements in project duration and resource utilization efficiency compared to conventional methods. Validation using three real-world highway projects in Egypt confirmed the framework’s practical applicability, achieving efficiency improvements of up to 80%. This research offers a data-driven, adaptable approach to repetitive project planning, providing planners with a robust tool to mitigate uncertainties and optimize project outcomes.https://doi.org/10.1038/s41598-025-12779-wPlanning efficiencyRepetitive projectsHighway projectsMonte carlo simulationStochastic modelingResource allocation optimization |
| spellingShingle | Ahmed M. Ebid Taher Ammar Ibrahim Mahdi Hosam Hegazy Evaluating the planning efficiency for repetitive construction projects using Monte Carlo simulation technique Scientific Reports Planning efficiency Repetitive projects Highway projects Monte carlo simulation Stochastic modeling Resource allocation optimization |
| title | Evaluating the planning efficiency for repetitive construction projects using Monte Carlo simulation technique |
| title_full | Evaluating the planning efficiency for repetitive construction projects using Monte Carlo simulation technique |
| title_fullStr | Evaluating the planning efficiency for repetitive construction projects using Monte Carlo simulation technique |
| title_full_unstemmed | Evaluating the planning efficiency for repetitive construction projects using Monte Carlo simulation technique |
| title_short | Evaluating the planning efficiency for repetitive construction projects using Monte Carlo simulation technique |
| title_sort | evaluating the planning efficiency for repetitive construction projects using monte carlo simulation technique |
| topic | Planning efficiency Repetitive projects Highway projects Monte carlo simulation Stochastic modeling Resource allocation optimization |
| url | https://doi.org/10.1038/s41598-025-12779-w |
| work_keys_str_mv | AT ahmedmebid evaluatingtheplanningefficiencyforrepetitiveconstructionprojectsusingmontecarlosimulationtechnique AT taherammar evaluatingtheplanningefficiencyforrepetitiveconstructionprojectsusingmontecarlosimulationtechnique AT ibrahimmahdi evaluatingtheplanningefficiencyforrepetitiveconstructionprojectsusingmontecarlosimulationtechnique AT hosamhegazy evaluatingtheplanningefficiencyforrepetitiveconstructionprojectsusingmontecarlosimulationtechnique |