Urban infrastructure systems play essential roles in the smooth functioning of modern society but are also threatened by seismic hazards in the earthquake‐prone areas. Retrofitting critical components of those systems has been considered as the most frequently used mitigation strategy in both the literature and practice. The seismic retrofit budget is usually limited, then it needs to identify a set of critical components to be retrofitted, which is generally formulated as a seismic retrofit optimization problem. This article proposes a multi‐perspective modeling and solution framework for the seismic retrofit optimization of urban infrastructure systems, which allows choosing different performance measures including vulnerability, resilience loss and economic loss as the objective function. The proposed framework can be used to explore how different performance measures and the infrastructure interdependencies affect the seismic retrofit decision. Taking the interdependent Shelby power and gas systems as an example, results show that if considering single systems, the optimal economic loss‐based performance improvement ratio (PIR) is larger than the best resilience loss‐based PIR, which is larger than the vulnerability‐based PIR; if considering interdependent systems, the interdependency intensity is indeed a key factor affecting the retrofit decision.

Earthquakes are among the most devastating natural disasters, posing a significant threat to human life and property. With the rapid pace of urbanization, urban risk against earthquakes has increased, making them an increasingly pressing concern for human society. Urban infrastructure systems (UISs), such as electric power, water supply, and gas systems, are essential to the smooth functioning of modern society but are highly vulnerable to ground shaking, resulting in service interruptions to customers and triggering negative impacts on society. This article focuses on the seismic retrofit problem, which intends to enhance the resilience of UISs against seismic hazards. First, a two-stage stochastic programming model is developed for the seismic retrofit problem, where the first stage seeks an optimal seismic retrofit strategy under a limited budget, and the second stage attempts to identify a repair sequence to maximize the system resilience under the given retrofit strategy. Then, this article introduces a heuristic algorithm based on the scenario reduction method and integer L-shaped method to solve the formulated model. Finally, numerical experiments on the Qujing power transmission system are conducted to validate the proposed algorithm. Results show that they can be applied to the resilience-based seismic retrofit problem of large-scale UISs.