[SCIP] pseudoboolean constraints

[James Cussens]

Hi all,

I would appreciate a bit more information on pseudoboolean constraints. In particular, I don't understand these arguments in SCIPcreateConsBasicPseudoboolean :

indvar  indicator variable if it's a soft constraint, or NULL
weight  weight of the soft constraint, if it is one
issoftcons      is this a soft constraint
intvar  a artificial variable which was added only for the objective function, if this variable is not NULL this constraint (without this integer variable) describes the objective function
I'm just relying on the doxygen documentation, perhaps this is explained in more detail elsewhere. It may be that setting them to non-NULL values might help me.

For context, the pseudoboolean constraints I'm using are like this:

z <= \sum_{i=1}^{n} [ x_i + y_i - 2*x_i*y_i ]

and only check and propagate are set to TRUE when they are created. On another matter, I see that 'and' variables are created for the x_i*y_i products. I've noticed that the associated and constraint is being separated even though it is being created from a constraint where initial and separate are set to FALSE which does not seem right to me. I certainly don't want the and relaxations in my LP since they don't help with the dual bound. I guess one way round this is to explicitly create non-separable and constraints  myself and use SCIPcreateConsPseudobooleanWithConss

James

James Cussens
Room MVB 3.26
Dept of Computer Science, University of Bristol
Phone: +44 (0)117 455 8723
https://jcussens.github.io/
Funded PhDs available in Bristol in the following areas: Data Science<http://www.bristol.ac.uk/cdt/compass/>, Interactive AI<http://www.bristol.ac.uk/cdt/interactive-ai/>, Cyber Security<http://www.bristol.ac.uk/cdt/cyber-security/> or Digital Health<http://www.bristol.ac.uk/cdt/digital-health/>.
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