Nobody talks about operations research today. But techniques that fell under that umbrella, like ARIMA and linear programming are still widely used, and aren’t going anywhere. (And it’s not without some irony that automated bulk time series forecasting is now sold as AI).

It's funny but at my last company, one of our systems used some linear programming to generate a model of physical processes.

The problem could have been tackled with greater accuracy using machine learning, but it would have taken a long time for the system to generate enough data points for a sound model and would have required more storage space. This was also complicated by the fact that the model had to be regenerated whenever the physical system being modeled was changed.

The linear programming solution was a lot cheaper and was "close enough" to serve as a useful approximation.

Linear and quadratic programming are amazing and totally underappreciated. Often they are the fastest way to get useful answers for problems (the solvers got really good over the past few decades).

What's OR?