Optimization, Risk Management and Adaptation for Integrated Infrastructure Systems under Technological and Policy Uncertainties

Regents Of The University Of Michigan - Ann Arbor, Ann Arbor MI

Investigators

Abstract

This award supports research on new models and a comprehensive framework to capture the complexities and interdependencies of infrastructure systems, while accounting for technological innovations and policy changes. Infrastructure systems, including energy, transportation, water, and telecommunication, form the backbone of modern society and are becoming increasingly complex due to emerging technologies such as renewable energy and artificial intelligence, as well as rapidly evolving public policies. By creating new models, theories, and tools to understand how these systems interact and respond to change, the research aims to enhance system performance, improve resilience to risks, and promote more efficient resource utilization. The outcomes support the development of robust infrastructure systems that can advance economic growth, public safety, and disaster risk reduction. The project also involves students in hands-on research and produces open-access educational tools to inspire the next generation of engineers and planners. Research findings will be broadly disseminated through publications, open-source code, shareable datasets, presentations, and cross-disciplinary collaborations. This research addresses the challenge of designing and operating interconnected infrastructure systems under uncertainty in future technological and policy directions. The project employs a broad set of methodologies, including network optimization, stochastic and robust optimization, and reinforcement learning, to develop scalable and reliable approaches for system integration and risk management. The research advances the field in three primary directions: (1) enabling dynamic and sequential modeling of design and operational decisions in integrated infrastructure systems; (2) identifying optimal or near-optimal solutions to complex system behaviors under both exogenous and endogenous uncertainties; and (3) evaluating the resilience, efficiency, and reliability of integrated systems through model validation and simulation. The models and algorithms are demonstrated in two key application domains: (i) the integration of power and transportation systems, and (ii) the coordinated monitoring, planning, and operation of multiple infrastructure networks. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.