Choosing a tool can be hard
Optimisation solvers are complex and incredibly powerful pieces of software. However, there are lots of different options and choosing which to use can be a daunting task.
Hacker-news has started to become a bit of a Reddit style troll swamp (as all online communities do eventually?). However, it still does have some really useful technically focused content. Last week there was a question about optimisation solvers that sparked a great discussion. It also included some interesting bits of history of the field.
Some options are:
Personally, I have used Google's OR-tools, for vehicle routing optimisation and found it very powerful. However, it is poorly documented with an inconsistent API. I've also used R's optim function and lpsolve for linear and integer problems. I rarely use closed source software, so have avoided the commercial tools, but I assume they must have advantages that justify their high price.