When I used to avidly leverage algebraic programming languages for Supply Chain optimization modeling, my language of choice was AMPL. Last weekend I had the opportunity to read these two awesome posts from Peter Cacioppi and I think I agree with him. For individuals who leverage algebraic programming languages heavily, I will suggest them to read these posts.
It does make sense to make your codes vendor neutral and Python looks like the way to go. In order to stay current with latest Analytical tools and trends, I recently took few Data science courses from Harvard University (extension school) and the coursework leveraged Python heavily. It was fun and insightful to explore the power of Python but I have never used Python for MIP (yet!), so I think its now time for me to deep dive into using Python for MIP. In last few years I have moved to more strategic aspects of Analytics but as an Analytics professional, one needs to keep their tools and tool chest updated. These recent developments in Algebraic programming landscape emphasize a point that I always make-Analytics professionals need to be continuous learners as the field of Analytics moves at a rapid pace.
Once I have some success in doing some intricate MIP programming in Python, I will probably publish my experience on this blog.
Disclaimer: This is a personal blog site and views and perspectives expressed here are solely my own and do not express the views or opinions of my employer.