Deep reinforcement learning approach for dynamic capacity planning in decentralised regenerative medicine supply chains

Research article (International Journal of Production Research, 2023) · cited 10× · AI/ML
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Deep reinforcement learning approach for dynamic capacity planning in decentralised regenerative medicine supply chains

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Deep reinforcement learning approach for dynamic capacity planning in decentralised regenerative medicine supply chains is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Deep reinforcement learning approach for dynamic capacity planning in decentralised regenerative medicine supply chains. Retrieved May 24, 2026, from https://4ort.xyz/entity/deep-reinforcement-learning-approach-for-dynamic-capacity-planning-in-decentralised-regenerative-medicine-supply-chains
MLA “Deep reinforcement learning approach for dynamic capacity planning in decentralised regenerative medicine supply chains.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/deep-reinforcement-learning-approach-for-dynamic-capacity-planning-in-decentralised-regenerative-medicine-supply-chains.
BibTeX @misc{4ortxyz_deep-reinforcement-learning-approach-for-dynamic-capacity-planning-in-decentralised-regenerative-medicine-supply-chains_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Deep reinforcement learning approach for dynamic capacity planning in decentralised regenerative medicine supply chains}}, year = {2026}, url = {https://4ort.xyz/entity/deep-reinforcement-learning-approach-for-dynamic-capacity-planning-in-decentralised-regenerative-medicine-supply-chains}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Deep reinforcement learning approach for dynamic capacity planning in decentralised regenerative medicine supply chains — https://4ort.xyz/entity/deep-reinforcement-learning-approach-for-dynamic-capacity-planning-in-decentralised-regenerative-medicine-supply-chains (retrieved 2026-05-24)

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