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I am wondering if there is any attempts of combining OR and ML in the following way. Priority-based rules are widely used in Resource Constrained Project Scheduling Problems. Is there a way to train a ML model to choose which priority rule to use? This may be done in advance depending on the structure of the input data or even while scheduling (i.e first using a priority rule then make a partial schedule using it then changing the priority rule etc.)

If it's the case, could you provide a link to papers and, if possible, a brief description of the idea behind (I am not familiar with ML at all)

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