3 ms·
There are many many successful applications. Yes, production scheduling has proven to be "resistant" towards mathematical optimization. But many other engineeri
by jpfr 10y ago
There are many many successful applications. Yes, production scheduling has proven to be "resistant" towards mathematical optimization. But many other engineering disciplines rely on it heavily.
Take for example model predictive control aka receding horizon control.
Control people have always built formal models of their systems. And now they use optimization theory where the systems don't fit the old linear quadratic controller paradigm very well.
You drive a car with traction control? Chances are that some embedded system is solving an optimization problem at kilohertz speed so you stay safe when turning on the road.
- shoo 10y agoi was thinking vaguely that the successful applications might be more likely to pop up in scenarios where problems can be clearly defined and are unlikely to change. i've worked on optimisation projects in business contexts where the requirements and the problems tend to change somewhat from month to month - this doesn't make for relaxing / hugely successful projects if the requirements changes bend the problem into territory that breaks the effectiveness of the solution approach.
- graycat 10y agoYup. In the real world, it tends to change. Then it can be tough for the computing, with or without optimization, to keep up. Yup.