Bridges are critical components of transportation infrastructure, serving as essential links within road networks and enabling mobility, economic activity, and emergency response. However, their safety, reliability and functionality are increasingly compromised by aging, structural deterioration, and exposure to multiple interacting hazards such as earthquakes and floods. Climate change exacerbates these challenges by intensifying the frequency and severity of hazards and accelerating material degradation, resulting in significant disruptions to traffic flow, connectivity, and the resilience of bridge networks. These disruptions not only affect local mobility but also have far-reaching implications for supply chains, business operations, and disaster recovery efforts.

This study introduces a resilience-based probabilistic framework for the life-cycle management of bridge networks under uncertainty. The framework accounts for the dynamic interplay of aging, multi-hazard exposure, and evolving travel demand, particularly during recovery periods following extreme events. By integrating multi-objective optimization techniques and adaptive recovery strategies, the framework enables decision-makers to prioritize retrofitting, and repair activities. It also incorporates dynamic travel demand modeling to optimize resource allocation while addressing changing traffic patterns and connectivity restoration. Application of this framework to transportation networks demonstrates its ability to enhance disaster resilience and long-term functionality by reducing vulnerability, improving recovery efficiency, and ensuring cost-effective use of resources. The results highlight the importance of proactive and adaptive infrastructure management to sustain safety, mobility, and economic stability under the combined pressures of aging infrastructure and a changing climate.