Note: This article is the first in a four-part series on GPU acceleration for optimization. We’ll begin here at a high level, with a focus on why GPUs matter for business decision-making and where they can make the most impact. Later posts will go progressively deeper into the math,...

If you work in operations long enough, you’ll hear the question: “Which is better — simulation or optimization?” It’s a bit like asking, “Which is better — a map or a test drive?” A map/optimization tells you the shortest route; a test drive/simulation shows you what traffic and potholes are...

"There are not many men who understand the theory underlying the economic size of lots" —FW Harris Today we celebrate the birthday of Ford W. Harris, a production engineer whose 1913 article, How Many Parts to Make at Once, quietly laid the foundation for one of the most enduring...

When building an optimization model, the first question is usually: “What are we trying to optimize?” Lower costs? Faster delivery? A more resilient network? But not all models need an objective. Sometimes, the goal is simply to answer: “Is any valid solution possible?” In business, these are known as feasibility-only...

The NFL just released its schedule for the upcoming season — a moment of excitement for fans and a jaw-dropping example of complex decision-making for those of us in the world of optimization. Behind the scenes, over 100,000 yes/no decisions are made to determine who plays whom, when, and where....

This week I had the opportunity to attend the INFORMS Analytics+ Conference in Indianapolis—a gathering of industry professionals, academics, and thought leaders exploring the future of analytics, optimization, and AI. It was a mix of sharp insights, witty commentary, and honest reflection on where our field is headed. Below are...

Over time, optimization solvers have become dramatically faster and more powerful—but paradoxically, model run-times haven’t always decreased. Why? Because as computational power increases, so do our ambitions. We add more products, more time periods, more constraints, and more real-world nuance. Models that once included a dozen decision variables now include...

Every March, 64 college basketball teams punch their ticket to the Big Dance—March Madness. While the bracket brings plenty of drama on the court, there’s another part of the tournament that gets less attention: how far teams have to travel for their first-round games. We wondered: what if we...

March 21, 2025 When the SimpleRose engineering team went looking for a guide on how to deploy cuOpt for our specific needs, none existed because the technology is so groundbreaking. We wished when we did an internet search for how to get started we found an article exactly like...

March 18, 2025 Linear programming (LP) and mixed-integer linear programming (MILP) are at the core of solving operations challenges, ranging from supply chain efficiency to workforce scheduling. These problems are notoriously complex and computationally demanding. To tackle these problems, SimpleRose and NVIDIA have joined forces to deliver cutting-edge optimization solutions...