What is the obvious advantage of using AMPL?

Question

I am doing a project using CPLEX solver, on Netbeans with Java. We have several optimization problems to solve, I have already solved one of them by coding in Java all the constraints, objective and variables, without using AMPL. However, some people in my team want to use AMPL.
Thus, as I don't want to read all the AMPL book to find the answer, is there an obvious reason to rather use AMPL than coding all the constraints "manually"? Moreover, can AMPL be integrated in Netbeans ? I did not find any documentation about that. Is AMPL useful when the constraints need to be "flexible" (I mean, we can't guess in advance the exact number of constraints, it depends on the parameters fixed by the user, modularity is a high importance factor...)

I am really curious to hear about that soon !

Thanks for help

Answer 1

You have just coded an optimisation model to optimise your company's production of widgets. Your company got a really good deal on $SOLVER1 so that's what you're using.

Over the next ten years, you improve and extend that model as your bosses throw new requirements at you. By the end of that time, you may have tens of thousands of lines of optimisation code as part of a system that, by now, is absolutely critical to your company's operations.

Your company's original licensing deal has expired, and the manufacturers of $SOLVER1 have massively increased the licensing fees, so you're now paying hundreds of thousands a year in licensing costs.

Meanwhile, the boffins at a rival company have just released a new version of $SOLVER2. It has fancy new algorithms that could solve the widget optimisation problem 20% faster and find better solutions than $SOLVER1 is giving you. It doesn't cost any more than $SOLVER1 and the performance is better.

Meanwhile, the open-source community has released $FREESOLVER. It might not be quite as powerful as the top commercial options, but it's as good as $SOLVER1 was ten years ago, and if you weren't paying $100k/year for licensing you could rent an awful lot of server time to make up for it.

...so, did you write your optimisation model on a platform that lets you switch to a new solver and take advantage of these opportunities without having to jettison ten years' worth of code?

There are huge advantages to being able to switch solvers quickly and easily. I know of one company who uses three different solvers for their work: they try two different open-source solvers both running in the cloud, and if neither of those can find an adequate solution then they throw it to an expensive solver with smarter algorithms. The open-source solvers handle 90% of their problems, so they only have to use the commercial solver for the last 10%, which allows them to make significant savings on their licensing costs.

One option we've discussed at my work is to use a commercial solver for mission-critical work, and open-source alternatives for applications like training or small-scale prototyping where we don't have the same requirements. That way we can minimise the number of concurrent users we need to license for the commercial solver.

(And, yes, there is still an issue of lock-in with the platform, but platforms like AMPL are significantly cheaper than a high-end commercial solver.)

Answer 2

AMPL is an algebraic modeling language and quoting from that link:

One advantage of AMPL is the similarity of its syntax to the mathematical notation of optimization problems.

For example, this can allow you to define groups of constraints without knowing in advance the dimensions of the model. And, perhaps, you can make big changes to your model more quickly. (You'll have to think about how often you will actually do that.)

However, one could argue that the "obvious advantage" of AMPL is that it supports dozens of different solvers. You can create your model and solve it with CPLEX, but then decide that you want to use a different solver (e.g., Gurobi, Xpress, etc.). On the AMPL Solvers web page, they have the following recommendation:

We recommend that you then test alternative solvers to determine which offers the best tradeoff of price and performance for your needs.

The AMPL API web page says that there is a Java API, so that should allow you to include it in a Netbeans project, but I have no experience with that.

At the end of the day, you could also argue that these "advantages" are a matter of taste. Using the CPLEX Java API directly, as you have already done, is certainly a valid solution if it meets your requirements. It may allow you to build the model more efficiently, use solver-specific/advanced features that might not be supported by AMPL, and to have more fine-grained control over the model formulation.