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A reinforcement learning approach to the stochastic cutting stock problem
We propose a formulation of the stochastic cutting stock problem as a discounted infinite-horizon Markov decision process. At each decision epoch, given current inventory of items, an agent chooses in which patterns to cut objects in stock in anticipation of the unknown demand. An optimal solution c...
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| Hauptverfasser: | , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Elsevier
2022-01-01
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| Schriftenreihe: | EURO Journal on Computational Optimization |
| Schlagworte: | |
| Online Zugang: | http://www.sciencedirect.com/science/article/pii/S219244062200003X |
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