A DGCNN predicts feasibility of TUSP instances during local search to abort unpromising runs early and reduce computation on real Dutch rail data.
Data mining and knowledge discovery 29(3), 626–688 (2015)
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Data-driven Policy on Feasibility Determination for the Train Shunting Problem
A DGCNN predicts feasibility of TUSP instances during local search to abort unpromising runs early and reduce computation on real Dutch rail data.