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I often think of SAT as the assembly language of discrete optimization.

I specify my problems in a higher-level DSL and a library then "compiles" it to SAT, where many solvers are available.




You should look into integer linear programs. They are a much useful "DSL" for discrete optimization. You get a lot of insight into flow problems from studying their LPs, for example, and it's very easy and efficient to solve flow problems with additional constraints using ILPs. Also, the state of the art for solving TSP and related hard path-finding problems uses techniques from integer linear programming.


You are correct. (I am very familiar with LP as well)




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