Mohamed Ahmed Gouda, Alqahtani Fahad K, Ismail ElHassan Reda, Nabawy Mohamed
Construction Engineering and Management Programme, Civil Engineering, The British University in Egypt, Cairo, Egypt.
Department of Civil Engineering, College of Engineering, King Saud University, P.O.Box 800, 11421, Riyadh, Saudi Arabia.
Sci Rep. 2025 Feb 7;15(1):4634. doi: 10.1038/s41598-025-88760-4.
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.
本研究识别出一个关键的知识缺口，揭示了道路状况的恶化（因广泛使用及其他因素而加剧）如何对道路网络的功能构成重大风险。若没有强有力的资金分配和优先排序策略，这种风险的程度可能会被忽视，从而对关键基础设施要素的性能产生不利影响。我们的研究引入了一种针对现有道路基础设施的综合决策模型，以弥补这一缺口。这种创新方法将基于地理信息系统（GIS）的道路管理模型与资金分配优先排序策略相结合，并通过遗传算法由一个优化引擎进行强化。其主要目标是精确确定针对道路状况的养护与维修（M&R）干预措施，从而提高路段的路面状况指数（PCI）。该研究围绕三个关键目标展开：（1）开发一个基于GIS的详细道路管理数据库，纳入道路基础设施的检查数据和属性，以进行主动的养护与维修决策；（2）有效分配资金，以维持在路况恶化道路上的服务提供；（3）确定养护与维修干预措施的最佳类型和时机，以提升路段的状况和性能。预期结果将为资产管理者提供一个全面的决策支持系统，以实施有效的养护与维修实践。
