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Each edge outgoing a node have a probability attached. Sometimes, we want to have them not sum up to one for modelling a discounting factor. While this makes sense when averaging the objective to make the cut, it is a bit less natural when sampling the edge. A dummy node with zero objective and no constraint can be used to model the discounting factor also. The solve on this node does not have to call any LP solver and can be made a special case in the modelling part.
We need to decide whether
- It complicates the solver part if we allow sum of the probabilities not to sum up to one: 👍
- Even if it complicates it, it allows to handle discounting faster because there is no dummy node : ❤️
blegat, frapac and joaquimg
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