Scheduling Repair Resources for Post‐Disaster Critical Infrastructure Systems: A Review of Models and Algorithms

Natural hazards such as earthquakes, floods, and tropical cyclones pose significant threats to the operation of critical infrastructure systems (CISs) in urban environments. Rapid recovery of post-disaster CISs is essential not only for mitigating immediate socio-economic impacts but also for strengthening urban resilience against future shocks. A key challenge in this recovery process is the efficient scheduling of resources to repair damaged infrastructure, a task complicated by the dynamic and uncertain post-disaster environment, the interdependencies within infrastructure networks, and the diverse priorities and demands of various stakeholders. Given the multifaceted nature of these challenges, numerous repair resource scheduling models have been developed, each incorporating distinct algorithmic strategies tailored to different disaster types and infrastructure systems. Despite a growing body of literature on optimization problems in disaster recovery, a comprehensive understanding of the variations in these models and methods remains lacking. This review aims to systematically explore and synthesize the landscape of repair resource scheduling models, highlighting model variants and their solution algorithms. In particular, it addresses the emerging challenges in post-disaster recovery, exacerbated by the coupled effects of climate change and rapid urbanization. By categorizing the variants and extensions of existing models, this study seeks to refine current frameworks and inspire the development of more comprehensive models, ultimately contributing to more informed restoration decisions and enhanced resilience of urban infrastructure systems.