If this is of interest to you, I can recommend the Coursera courses. They are very effective for introducing both MiniZinc and constraint-based modeling of problems.
I’ve used it for smaller problems ranging from toys and puzzles to small scale optimization and scheduling problems.
In the latter, my biggest use was to prototype how I’d solve a problem for my sister in her job (scheduling facilities maintenance in a way that didn’t interfere with planned experiments and tests, what maintenance work could be done and when to minimize conflicts with customer schedules). It worked as an example but couldn’t handle the full factors (well, my laptop and lack of experience optimizing models) and they continued relying on (mostly) human judgement (worked out well enough).
I also used it to make a soccer schedule. It worked better than my teammates attempt at making a scheduler from scratch (building both the solver and model). There are already systems for this that the league had available, it was more a “can I do this” challenge.
More important, to me, was learning about a class of solvers and what problems they were effective at solving. Even though I have no immediate need it expanded my knowledge so I know where to start in the future rather than (foolishly) starting from scratch. Or I can point others to it. I’ve seen many devs (myself at times too) reinvent the wheel because we don’t know what options are out there. I took the course to combat that behavior in myself and to better guide colleagues, plus it was fun.
(Apologies, on mobile. I have a few more paragraphs I could write but this is not the easiest entry mechanism for that.)
MiniZinc should've let you farm out your problem to CBC if it could be made into an LP or MIP problem. CBC isn't as good as CPLEX or GUROBI, but is great free software that can run massive scale models.
I just never explored it past the point of trying out the ideas on my laptop. I knew it could be done (and should've mentioned that in my prior post), but had no immediate need to. Their scheduling solutions were effective, though suboptimal (at my sister's job). Additionally, as I spoke with her more I found out there were a lot of factors I didn't know about (and some I couldn't be told about for various reasons). I love my sister, and it was a good learning experience, but I can only work pro bono for so long. She had no support from her leadership to explore this approach further so that was that.
