Can I include continuous variable when optimising with CPMpy?

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I need to run a model, where I optimise a diet within a set of constraints and call all integer solutions in the end. I have found a diet example matching almost what I need here: hakank.org. However, in my case, my variables take continuous values, so in the examples this would be all the nutritional values and the cost, while only x take integer. However, it seems like I can only define either 'intvar' or 'boolvar' when defining by variables with this model. Is there a way to overcome this? Other would there be other more suitable models with examples that I can read online?

I'm new to constraint programming, so any help would be appreaciated!

Thanks.

cpm continuous linear-programming constraint-programming python
2 Answers

Most Constraint Programming tools and solvers only work with integers. That is where their strength is. If you have a mixture of continuous and discrete variables, it is a good idea to have a look at Mixed Integer Programming. MIP tools and solvers are widely available.

The diet model is a classic example of an LP (Linear Programming) Model. When adding integer restrictions, you end up with a MIP model.

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To answer your question: CPMpy does not support float variables (and I'm not sure that it's in the pipeline for future extensions).

Another take - than using MIP solvers as Erwin suggest - would be to write a MiniZinc (https://www.minizinc.org/) model of the problem and use some of its solvers. See my MiniZinc version of the diet problem: http://hakank.org/minizinc/diet1.mzn. And see the MiniZinc version of Stigler's Diet problem though it's float vars only: http://hakank.org/minizinc/stigler.mzn.

There are some MiniZinc CP solvers that also supports float variables, e.g. Gecode, JaCoP, and OptimathSAT. However, depending on the exact constraints - such as the relation with the float vars and the integer vars - they might struggle to find solutions fast. In contrast to some MIP solvers, generating all solutions is one of the general features of CP solvers.

Perhaps all these diverse suggestions more confuse than help you. Sorry about that. It might help if you give some more details about your problem.

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