Every year, natural disasters cause infrastructure damages and power outages that have considerable impacts on both quality of life and economic welfare. Mitigating the effects of disasters is an important but challenging task, given the underlying uncertainty, the need for fast response, and the complexity and scale of the infrastructures involved, not to mention the social and policy issues. This talk describes how to use planning and scheduling technologies to address these challenges in a rigorous and principled way. In particular, we present the first optimization solutions to last-mile disaster preparedness and recovery for a single commodity (e.g., water) and for the electrical power network. The optimization algorithms were compared to existing practice on disaster scenarios based on the US infrastructure (at the state scale) and generated by state-of-the-art hurricane simulation tools. Some of our algorithms are deployed as part as the Los Alamos National Laboratories operational tools and provide recommendations to the U.S. Department of Homeland Security.