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Learning heuristic selection using a Time Delay Neural Network for Open Vehicle Routing
2017
2017 IEEE Congress on Evolutionary Computation (CEC)
A selection hyper-heuristic is a search method that controls a prefixed set of low-level heuristics for solving a given computationally difficult problem. This study investigates a learning-via demonstrations approach generating a selection hyper-heuristic for Open Vehicle Routing Problem (OVRP). As a chosen 'expert' hyper-heuristic is run on a small set of training problem instances, data is collected to learn from the expert regarding how to decide which low-level heuristic to select and
doi:10.1109/cec.2017.7969477
dblp:conf/cec/TyasnuritaOJ17
fatcat:6kdmphcomvdejna2jljnrzrbxu