Gino Lim remembers the moment Hurricane Harvey submerged Houston’s streets and crippled its power grid—homes dark for days, hospitals on backup generators, roads impassable. As floodwaters rose, so did a question that now drives his work: If we can’t protect everything, what should we protect first? A mathematical model developed by Lim, the R. Larry and Gerlene (Gerri) R. Snider Endowed Chair of Industrial and Systems Engineering at the University of Houston, is offering cities a smarter way to answer that question. With climate-driven disasters growing more frequent and budgets tighter than ever, Lim’s framework helps utilities, transportation agencies, and city planners invest resilience dollars where they’ll do the most good—before the next storm hits.
The challenge isn’t just about spending money; it’s about spending wisely. Decision-makers rarely know how intense the next disaster will be, which bridges or substations will fail, or how long recovery will take. Traditional planning often relies on single-scenario forecasts, leaving systems vulnerable to surprises. Lim’s model, published in Computers & Industrial Engineering, takes a different approach: it embraces uncertainty. Using chance-constrained optimization, it evaluates hundreds of possible disaster outcomes and identifies the investments most likely to keep critical infrastructure running or restore it quickly. This means agencies can now prioritize upgrades with statistical confidence, not guesswork.
Working with Jian Shi, associate professor of electrical power engineering technology, and doctoral student Tugce Uslu Aktas, Lim tested the model on real-world electric power and transportation networks in vulnerable urban areas like Houston. The results were striking: by focusing on just a small number of high-leverage assets—such as key substations or traffic control hubs—cities could dramatically improve system-wide resilience. In one simulation, strategic investments in fewer than 10% of critical nodes increased the probability of maintaining essential services by over 40% during extreme events. That kind of efficiency is transformative for cities operating under tight fiscal constraints.
The broader impact extends beyond infrastructure. When power stays on and roads remain passable, hospitals function, supply chains hold, and communities recover faster. Lim’s model doesn’t just prevent damage—it preserves lives and livelihoods. As extreme weather becomes the norm, the ability to answer two fundamental questions—how much to invest, and where—has never been more urgent.
This isn’t a one-size-fits-all solution, but a flexible tool adaptable to cities worldwide facing floods, wildfires, or hurricanes. For Lim, the goal is clear: "Our work helps decision-makers get the greatest resilience benefit from every dollar invested." That principle could soon guide how cities from Miami to Manila prepare for an uncertain future—one smart investment at a time.