I asked about integer programming before on CV and it was locked as off topic. I'm unable to find a site dedicated to math programming and optimisation on stack exchange. Any one has idea?
Optimization per se isn't part of our site's interests. Like Calculus, Linear Algebra, Computer Science, and other disciplines, it is a tool we use, respect, and enjoy, but is not otherwise of interest in its own right. So, just as we tend to send pure Calculus, pure Linear Algebra, etc. questions (which do not have any explicit connection to statistics or machine learning) over to Mathematics, we will also close pure optimization questions. And just as we sometimes do answer questions about Calculus, etc., when they are clearly addressing a topic in statistics or machine learning, we sometimes answer optimization questions. But that's rare.
There are two places to look for communities that would answer pure optimization questions:
Existing SE sites. Use the menu at the top to filter by category. I don't see any good candidates for general questions about optimization. However, some sites will field suitably framed questions of that nature, such as
Math Overflow (for research-level questions in optimization techniques, perhaps),
Mathematics (primarily for elementary problems, such as Lagrange multiplier questions, etc.),
Mathematica (which is interested in computer solutions using Mathematica--which despite the apparent narrowness can be an effective way to get answers, because Mathematica programs frequently are like executable mathematics), and especially
A more extensive look (which requires browsing through a hundred Beta sites, unfortunately) also turns up Data Science, which might like to address certain kinds of techniques that are used in data mining.
Proposed SE sites ("Area 51"). I searched for "Optimization" and found nothing. If you're energetic and dedicated you might consider starting a proposal.
To expand on the on-topic side of @whubers answer:
Firstly, there are applications of optimization that are on topic here: both optimization applied to the "usual" fitting of models and hyperparameter optimization.
Secondly, I think one fundamental difference between CV and more "mathematical" sites is that stats is about noisy data. In contrast most optimization heuristics I'm familiar with assume well behaved smooth target functions. So I'd also conster questions about optimization of noisy target functions on topic.