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SOLO: Search Online, Learn Offline for Combinatorial Optimization Problems
[article]
2021
arXiv
pre-print
We study combinatorial problems with real world applications such as machine scheduling, routing, and assignment. We propose a method that combines Reinforcement Learning (RL) and planning. This method can equally be applied to both the offline, as well as online, variants of the combinatorial problem, in which the problem components (e.g., jobs in scheduling problems) are not known in advance, but rather arrive during the decision-making process. Our solution is quite generic, scalable, and
arXiv:2104.01646v3
fatcat:mzprf47ajjg2bkxeesfwfor6ym