We know there are a range of solvers, free and paid, to choose from. We also know that for some situations, a free solver might be all that you need. This article is designed to help you better understand what type of linear programming solver is right for you.
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The nice thing about open source packages is that it’s easy to get started, because you can download and install them immediately. But these packages are typically behind the state of the art in optimization, and can often fail to find an optimal solution within a reasonable timeframe.
What does it mean to fail? Sometimes the free solvers reach the 1,000-second time limit before optimizing the problem. But in some cases, the solvers report an incorrect solution or falsely conclude that a problem was infeasible.
Unfortunately, when people experience slow performance with free solvers, they often give up on optimization technology altogether.
Despite the limitations described above, we don’t mean to give you the impression that free solvers are never the right choice. Below are a few scenarios where you may want to consider a free solver.
Often times, when a company is first looking at using an optimization solver in their business, there may not be an approved budget. Management may still be trying to determine the role optimization can play in planning and decision-making, and the team doing the work is still “getting their feet wet.”
Most free solvers are written in C or C++ and don’t offer other APIs. Gurobi offers both C and C++ APIs, as well as a full range of other APIs, including Python.
Free solvers tend to struggle with larger and more difficult models, but if a free solver is able to solve your problem now, and you are confident that your problem won’t become more difficult in the future, then a free solver could be a reasonable choice.
We want to stress that you should consider future growth in the model. We’ve seen many situations where free solvers worked well on a small prototype but were unable to handle the production model. This can cause a lot of rework that you may be able to avoid.
Before you make the choice to use a free solver, we suggest that you look at relative performance on models of similar size and complexity to those that you are likely to want to solve eventually. We are happy to assist if you like. We have a very large library of models and may be able to run a specific comparison.
One of the most important questions people tend to ask when they are first exploring solvers is if optimization is a fit for their business. We have seen cases where someone selected a free solver, tried building a model, and the solver just couldn’t handle the problem. As a result, they assumed their problem was just too complex to use optimization techniques.
Others find free solvers just too hard to use, given the solver didn’t support the programming language they preferred, they couldn’t get support, etc. The team then ends the project and moves on. This is unfortunate since, with the right tools and support, the project might have been a great success. If you find yourself in this situation, please contact us. We may be able to help steer you in the right direction so you get the results you need to support continuing with the project.
It’s great that it’s easy to get started with open-source tools, but you should approach them with your eyes open. For example, if an open-source tool is unable to solve your model, you shouldn’t assume that your project is hopeless.
Additionally, a state-of-the-art commercial solver can save valuable development time in several ways. First, the interfaces in commercial solvers are typically more polished and advanced than those in open-source tools. For example, the Gurobi Python interface brings a modeling syntax to the popular Python language. Second, commercial systems like Gurobi offer pre-built IT infrastructure like client-server options and cloud computing.
There are several important differences between free and commercial solvers you should keep in mind:
| Solver Class | Detail |
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| Free Solvers |
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| Paid Solvers |
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