Ryan O'Neil led the Decision Engineering department at Grubhub and Zoomer, which owned forecasting, scheduling, routing, and simulation. Ryan worked as an Operations Research Analyst at MITRE, and led software teams at The Washington Post, Yhat, and Polimetrix. During this, he earned a PhD in Operations Research at George Mason University, and wrote his dissertation on real time routing for pickup and delivery problems.
CI/CD is how you ship higher quality code to production faster. But with decision science models, there’s a twist. We’ll look at the role of decision quality, specific testing tooling, and problem drift on CI/CD for decision science models.
Automating on-demand logistics operations for scale, customization, and iteration is easier than you might think. Learn how to build, test, and deploy models for demand forecasting, shift scheduling, and route creation.
The next era of optimization isn't about building a better solver. It's about collaborative, opinionated tooling that empowers teams to move faster with less confusion and more access to the decision technology ecosystem.
In the beginning there was linear programming. It spawned decades of similarly-shaped solver offshoots. Decision diagrams break with this classic paradigm and offer new opportunities to solve common optimization problems.
Nextmv is removing the roadblocks for going from optimization problem definition to production environment. This makes optimization easier for operations researchers and more accessible to developers. See what this looks like and watch a demo.