Resource Allocation Framework for Optimizing Long-Term Infrastructure Network Resilience
Jingran Sun, Zhe Han, Zhanmin Zhang
Abstract
With the increase in frequency and severity of extreme weather events, it is essential to incorporate the resilience of infrastructure networks into the decision-making process of resource allocation for maintenance planning. Considering that infrastructure systems are interdependent in nature, the impact of both extreme events and maintenance treatments on infrastructure resilience could be further amplified. Consequently, infrastructure interdependencies should be considered when analyzing the impact of extreme events and maintenance treatments. Additionally, uncertainties (such as uncertainties associated with the occurrence of extreme events and maintenance treatment effects) should also be into consideration. This paper proposes a resource allocation framework that incorporates these factors to optimize long-term resilience of infrastructure networks. The proposed framework capitalizes on integrating agent-based modeling with a double deep Q-network model to support decision-making in resource allocations; it allows infrastructure management agencies to maximize the long-term resilience of infrastructure networks while keeping their physical condition at an acceptable level. The results obtained from the case study show that the proposed framework is effective and can be customized to various local conditions.