First time I came across integer programming (and mathematical programming generally) was when studying hydroelectric power generation planning, for a masters I ended up not pursuing. Then, when selecting a masters in CS, I ended up working with an advisor who used mixed-integer programming applied to classic machine learning models (mainly optimal decision trees). A fascinating and widely applicable method, indeed!
I've always had the impression that Mathematical programming esp. Mixed integer programming/Integer programming is largely "unknown" outside of core engineering and operations research. It's an excellent framework to solve a whole host of problems that arise in business and elsewhere, which are solved using suboptimal (hah) heuristics instead.
Okay, maybe I was a bit harsh, but it definitely doesn't pop up as often as deep learning and statistical machine learning. For those who wish to get deeper into this, I highly recommend Optimization over Integers by Bertsimas and Weismantel.
Do modern compiler (register allocation/ instruction generation) involve some kind of integer programming or constraint solving? I vaguely remember compilers using Z3 solver
Does anyone know what the state of the art industry solvers do for these problems? I had dabbled a bit in ml approaches to combinatorial optimization with great interest a few years back, but I don't think any of these rl based methods ended up being used in production.
One thing I discovered on 8080 was that 0FFFFH is "infinity". Meaning it is better to produce this infinity than zero-division error, when system is oscillating around zero. Otherwise you have to insert zero-tests everywhere and waste precious clock cycles.
10 comments
[ 4.7 ms ] story [ 27.9 ms ] threadOkay, maybe I was a bit harsh, but it definitely doesn't pop up as often as deep learning and statistical machine learning. For those who wish to get deeper into this, I highly recommend Optimization over Integers by Bertsimas and Weismantel.