Synergizing GIS and genetic algorithms to enhance road management and fund allocation with a comprehensive case study approach
Abstract This study identifies a critical knowledge gap, revealing how the deterioration of roads, compounded by extensive usage and additional factors, poses significant risks to the road networks’ functionality. Without a robust fund allocation and prioritization strategy, the extent of this risk...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-02-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-88760-4 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1823862126796603392 |
|---|---|
| author | Ahmed Gouda Mohamed Fahad K. Alqahtani ElHassan Reda Ismail Mohamed Nabawy |
| author_facet | Ahmed Gouda Mohamed Fahad K. Alqahtani ElHassan Reda Ismail Mohamed Nabawy |
| author_sort | Ahmed Gouda Mohamed |
| collection | DOAJ |
| description | Abstract This study identifies a critical knowledge gap, revealing how the deterioration of roads, compounded by extensive usage and additional factors, poses significant risks to the road networks’ functionality. Without a robust fund allocation and prioritization strategy, the extent of this risk may be overlooked, adversely affecting the performance of essential infrastructure elements. Our research introduces an integrated decision-making model for existing road infrastructures to address this gap. This innovative approach combines a Geographic Information System (GIS)-based road management model with a fund allocation prioritization strategy, enhanced by an optimization engine via a genetic algorithm. The primary aim is to precisely determine Maintenance and Repair (M&R) interventions tailored to the condition states, thereby improving the Pavement Condition Index (PCI) of the road segments. The research is structured around three key objectives: (1) develop a detailed GIS-based road management database incorporating inspection data and attributes of road infrastructure for proactive M&R decision-making; (2) efficiently allocate funds to maintain service delivery on deteriorated roads; and (3) pinpoint the optimal type and timing of M&R interventions to boost the condition and performance of the road segments. Anticipated results will provide asset managers with a comprehensive decision support system for executing effective M&R practices. |
| format | Article |
| id | doaj-art-1bd9a70df2884f779eb6167fe30838b2 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-1bd9a70df2884f779eb6167fe30838b22025-02-09T12:36:14ZengNature PortfolioScientific Reports2045-23222025-02-0115112110.1038/s41598-025-88760-4Synergizing GIS and genetic algorithms to enhance road management and fund allocation with a comprehensive case study approachAhmed Gouda Mohamed0Fahad K. Alqahtani1ElHassan Reda Ismail2Mohamed Nabawy3Construction Engineering and Management Programme, Civil Engineering, The British University in EgyptDepartment of Civil Engineering, College of Engineering, King Saud UniversityDepartment of Construction Management, College of Engineering, Louisiana State University (LSU)Faculty of Engineering, Construction Engineering and Management Programme, Civil Engineering, The British UniversityAbstract This study identifies a critical knowledge gap, revealing how the deterioration of roads, compounded by extensive usage and additional factors, poses significant risks to the road networks’ functionality. Without a robust fund allocation and prioritization strategy, the extent of this risk may be overlooked, adversely affecting the performance of essential infrastructure elements. Our research introduces an integrated decision-making model for existing road infrastructures to address this gap. This innovative approach combines a Geographic Information System (GIS)-based road management model with a fund allocation prioritization strategy, enhanced by an optimization engine via a genetic algorithm. The primary aim is to precisely determine Maintenance and Repair (M&R) interventions tailored to the condition states, thereby improving the Pavement Condition Index (PCI) of the road segments. The research is structured around three key objectives: (1) develop a detailed GIS-based road management database incorporating inspection data and attributes of road infrastructure for proactive M&R decision-making; (2) efficiently allocate funds to maintain service delivery on deteriorated roads; and (3) pinpoint the optimal type and timing of M&R interventions to boost the condition and performance of the road segments. Anticipated results will provide asset managers with a comprehensive decision support system for executing effective M&R practices.https://doi.org/10.1038/s41598-025-88760-4Asset managementGeographic information systemFund allocationMaintenance and repairPavement condition index |
| spellingShingle | Ahmed Gouda Mohamed Fahad K. Alqahtani ElHassan Reda Ismail Mohamed Nabawy Synergizing GIS and genetic algorithms to enhance road management and fund allocation with a comprehensive case study approach Scientific Reports Asset management Geographic information system Fund allocation Maintenance and repair Pavement condition index |
| title | Synergizing GIS and genetic algorithms to enhance road management and fund allocation with a comprehensive case study approach |
| title_full | Synergizing GIS and genetic algorithms to enhance road management and fund allocation with a comprehensive case study approach |
| title_fullStr | Synergizing GIS and genetic algorithms to enhance road management and fund allocation with a comprehensive case study approach |
| title_full_unstemmed | Synergizing GIS and genetic algorithms to enhance road management and fund allocation with a comprehensive case study approach |
| title_short | Synergizing GIS and genetic algorithms to enhance road management and fund allocation with a comprehensive case study approach |
| title_sort | synergizing gis and genetic algorithms to enhance road management and fund allocation with a comprehensive case study approach |
| topic | Asset management Geographic information system Fund allocation Maintenance and repair Pavement condition index |
| url | https://doi.org/10.1038/s41598-025-88760-4 |
| work_keys_str_mv | AT ahmedgoudamohamed synergizinggisandgeneticalgorithmstoenhanceroadmanagementandfundallocationwithacomprehensivecasestudyapproach AT fahadkalqahtani synergizinggisandgeneticalgorithmstoenhanceroadmanagementandfundallocationwithacomprehensivecasestudyapproach AT elhassanredaismail synergizinggisandgeneticalgorithmstoenhanceroadmanagementandfundallocationwithacomprehensivecasestudyapproach AT mohamednabawy synergizinggisandgeneticalgorithmstoenhanceroadmanagementandfundallocationwithacomprehensivecasestudyapproach |