A new training-free distance metric compares MILP instances by matching the proportions of variable-weight pairs in their constraints, and it groups problems by class almost as well as a supervised graph neural network.
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A Distance Metric for Mixed Integer Programming Instances
A new training-free distance metric compares MILP instances by matching the proportions of variable-weight pairs in their constraints, and it groups problems by class almost as well as a supervised graph neural network.