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However, I think there is a lack of comparison of solving time between different methods in the same instances.
Although the paper reports the number of nodes explored by learned and SCIP policies, the number of nodes and solving time are not exactly equivalent. Neural network policies maybe run faster than default SCIP policies with the same number of explored nodes.
A lot of people pay attention to ML4CO because of its potential to speed up solving MILP problems. It would be better and more intuitive that there is a solving time comparison, just like Exact Combinatorial Optimization with Graph Convolutional Neural Networks, Gasse et al.
The text was updated successfully, but these errors were encountered:
Great job! Very inspiring.
However, I think there is a lack of comparison of solving time between different methods in the same instances.
Although the paper reports the number of nodes explored by learned and SCIP policies, the number of nodes and solving time are not exactly equivalent. Neural network policies maybe run faster than default SCIP policies with the same number of explored nodes.
A lot of people pay attention to ML4CO because of its potential to speed up solving MILP problems. It would be better and more intuitive that there is a solving time comparison, just like Exact Combinatorial Optimization with Graph Convolutional Neural Networks, Gasse et al.
The text was updated successfully, but these errors were encountered: