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Paper Citation Record · LEDGER

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets

As of 18 August 2026, this Paper Citation Record lists 74 of 74 outbound references and 0 inbound Pith citation observations for arXiv:2505.11135.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.11135 v1

Coverage vector

measured 74 of 74 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:00:41.179308Z

measured 74 of 74 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

74 of 74 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a2298e5a-66b0-427e-a9d9-47527fff8fa5 · outbound

This paper cites Prod Eng Res Devel 14.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Prod Eng Res Devel 14

Reference 1

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Observation 0d34fbba-1b48-421c-81a0-e3de9b800281 · outbound

This paper cites INFORMS J Comput 3(2):149–156.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets INFORMS J Comput 3(2):149–156

Reference 2

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Observation ab57c65c-2904-4946-b662-07a38557bef1 · outbound

This paper cites Springer, Cham, Switzerland, https://doi.org/10.1007/978-3-030-41544-0.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Springer, Cham, Switzerland, https://doi.org/10.1007/978-3-030-41544-0

Reference 3

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Observation 96df64fc-7cda-41e8-8c92-cc5aba666c75 · outbound

This paper cites Applied Sciences 13(6):3615.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Applied Sciences 13(6):3615

Reference 4

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Observation afc68c6e-9766-46a3-9f4e-d70fe626ffd1 · outbound

This paper cites Optim Lett 8(4):1417–1431.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Optim Lett 8(4):1417–1431

Reference 5

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Observation b96cfc69-d3bc-4941-a984-219e4d76ff34 · outbound

This paper cites Springer, Berlin and New York, https://doi.org/10.1007/10.1007/978-3-540-69516-5.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Springer, Berlin and New York, https://doi.org/10.1007/10.1007/978-3-540-69516-5

Reference 6

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Observation 1507c7af-e052-48f2-8126-07905063ea9e · outbound

This paper cites SEMATECH Technical Transfer report 26.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets SEMATECH Technical Transfer report 26

Reference 7

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Observation 8383daf1-81fb-4ab8-a653-3c707fe3f982 · outbound

This paper cites Comput Ind Eng 162:107782.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Comput Ind Eng 162:107782

Reference 8

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This paper cites URL http://www.d-simlab.com/ category/d-simcon/products-d-simcon/forecaster-and-scenario-manager/.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets URL http://www.d-simlab.com/ category/d-simcon/products-d-simcon/forecaster-and-scenario-manager/

Reference 9

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Observation 6e0a90a2-257f-499c-9bfc-102c0d213b0e · outbound

This paper cites Operations Research Perspectives 9:100249.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Operations Research Perspectives 9:100249

Reference 10

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Observation 70b6c8b8-110f-48ac-a097-7cde33199eff · outbound

This paper cites Eur J Oper Res 109(1):137–141.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Eur J Oper Res 109(1):137–141

Reference 11

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Observation f9c7676f-d96b-46b1-8bfd-ecccccd0c7da · outbound

This paper cites In: Proceedings of 35th IEEE Conference on Decision and Control, vol 2.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets In: Proceedings of 35th IEEE Conference on Decision and Control, vol 2

Reference 13

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Observation 44202e82-f6d0-43d1-8b2a-0168b5d99093 · outbound

This paper cites In: 2009 International Conference on Computers & Industrial Engineering.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets In: 2009 International Conference on Computers & Industrial Engineering

Reference 14

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Observation 1d5afa51-b7dd-4e61-9eed-ab5a1f01e197 · outbound

This paper cites URL https://www.scopus.com, accessed: 2025-01-09.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets URL https://www.scopus.com, accessed: 2025-01-09

Reference 15

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 152555c4-3bf4-47a2-a1cd-8622acf79f54 · outbound

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Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Unresolved cited work

Reference 16

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Observation b49b65e1-e3f5-429d-8877-4d5bdf724d09 · outbound

This paper cites In: Hammer P, Johnson E, Korte B (eds) Discrete Optimization II, Annals of Discrete Mathematics, vol 5.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets In: Hammer P, Johnson E, Korte B (eds) Discrete Optimization II, Annals of Discrete Mathematics, vol 5

Reference 17

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Observation e81a15f4-8d1d-45a5-8110-444532dc6c3e · outbound

This paper cites The International Journal of Advanced Manufacturing Technology 27(11–12):1163–1169.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets The International Journal of Advanced Manufacturing Technology 27(11–12):1163–1169

Reference 18

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Observation 77f6df03-a73a-482a-a92d-93022a2d259b · outbound

This paper cites Evol Comput 9(2):159–195.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Evol Comput 9(2):159–195

Reference 19

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Reference 20

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This paper cites https://doi.org/10.1609/AAAI.V30I1.10295.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets https://doi.org/10.1609/AAAI.V30I1.10295

Reference 21

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Observation 3e1b2754-a025-45e0-b620-482ab30ba70c · outbound

This paper cites Production and Inventory Management Journal 38(4):51–57.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Production and Inventory Management Journal 38(4):51–57

Reference 22

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Observation 5c6e3ac3-5429-46e3-878e-b0f774474308 · outbound

This paper cites Vieweg+Teubner Verlag, Wiesbaden, Germany, https://doi.org/10.1007/ 978-3-8348-1994-9.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Vieweg+Teubner Verlag, Wiesbaden, Germany, https://doi.org/10.1007/ 978-3-8348-1994-9

Reference 23

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Observation a209c6ca-9986-4e67-ac60-e4a161d454a0 · outbound

This paper cites Eur J Oper Res 263(1):50–61.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Eur J Oper Res 263(1):50–61

Reference 24

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Observation 683bd1f3-e881-4c3b-b8a7-3126060bf918 · outbound

This paper cites IEEE Transactions on Semiconductor Manufacturing 33(4):522–.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets IEEE Transactions on Semiconductor Manufacturing 33(4):522–

Reference 25

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Reference 26

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Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Constraints 23

Reference 27

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Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Unresolved cited work

Reference 28

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This paper cites PhD thesis, University of California, Berkeley, USA.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets PhD thesis, University of California, Berkeley, USA

Reference 29

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Observation c8c1d834-09b9-4088-9499-2bb0141b5961 · outbound

This paper cites In: ICML, Proceedings of Machine Learning Research, vol 80.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets In: ICML, Proceedings of Machine Learning Research, vol 80

Reference 30

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Observation 2bb031b2-9443-43cb-8f97-293292524be5 · outbound

This paper cites In: IEA/AIE (2), Lecture Notes in Computer Science, vol 13926.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets In: IEA/AIE (2), Lecture Notes in Computer Science, vol 13926

Reference 31

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Observation 1ca44dcc-5dfb-46f8-a42b-d20e167abd0f · outbound

This paper cites IEEE Trans Autom Sci Eng 19(4):3659–3671.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets IEEE Trans Autom Sci Eng 19(4):3659–3671

Reference 32

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This paper cites IEEE Trans Cybern 53(10):6663–.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets IEEE Trans Cybern 53(10):6663–

Reference 33

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Observation 252e9bd9-4ba5-4d20-8b15-03585decf956 · outbound

This paper cites Complex & Intelligent Systems 8(6):4641–4662.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Complex & Intelligent Systems 8(6):4641–4662

Reference 34

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Observation b8d3ab30-af8e-4a07-80ca-ffdee054737a · outbound

This paper cites Eng Appl Artif Intell 133:108487.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Eng Appl Artif Intell 133:108487

Reference 35

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Observation 04ae368f-3073-4253-a023-95f7b72cbe5d · outbound

This paper cites Neural Comput Appl 35(30):22281–22296.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Neural Comput Appl 35(30):22281–22296

Reference 36

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source=pdf_text observed=2026-08-15T21:00:41.059379Z digest=sha256:b8d0bac4aa33fe03c6d3e0fce6c8db5dc5ddd82311f1a7cf0cd6955b77b13249

Observation e33e6f6d-9b35-488b-a386-8ad2d7605485 · outbound

This paper cites Journal of Scheduling https://doi.org/10.1002/jos.102.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Journal of Scheduling https://doi.org/10.1002/jos.102

Reference 37

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source=pdf_text observed=2026-08-15T21:00:41.062579Z digest=sha256:36b61f4adeb49f055d2af406d2c87da02b99ec646c94d6109980dd0a140766e3

Observation 7b1a1619-41e0-481c-9c8c-b3de06496fa1 · outbound

This paper cites Adv Eng Softw 69:46–61.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Adv Eng Softw 69:46–61

Reference 38

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Reference 39

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source=pdf_text observed=2026-08-15T21:00:41.069627Z digest=sha256:85f0a9f427dd073b4df5f682e14ea170d05dd9cc7893f98a01366d3273ebc51c

Observation 8c6a9745-53e1-4885-9975-7ec2ca0cd5b5 · outbound

This paper cites In: ICML, JMLR Workshop and Conference Proceedings, vol 48.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets In: ICML, JMLR Workshop and Conference Proceedings, vol 48

Reference 40

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source=pdf_text observed=2026-08-15T21:00:41.073218Z digest=sha256:00294244508f74037f1b077b9d8ecf65d5d89307840c1bbca973c1278c9d3929

Observation 5cae60ec-4ce1-4916-bec6-1389148cda8f · outbound

This paper cites J Sched 14(6):583–599.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets J Sched 14(6):583–599

Reference 41

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Observation 9a9d32a5-115c-4114-a7d7-25e23d344435 · outbound

This paper cites Springer, Cham, Switzerland, https://doi.org/10.1007/978-1-4614-4472-5.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Springer, Cham, Switzerland, https://doi.org/10.1007/978-1-4614-4472-5

Reference 42

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Observation e5e7f059-452d-47d6-a197-62a081294c98 · outbound

This paper cites IEEE Trans Autom Sci Eng 29 17(3):1420–1431.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets IEEE Trans Autom Sci Eng 29 17(3):1420–1431

Reference 43

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source=pdf_text observed=2026-08-15T21:00:41.082513Z digest=sha256:508fb623d7c43e22f44a29bfb575318fe64f6012d52c560b98b539a27524bb8c

Observation ad78b662-f286-4249-b0f6-d068f857fcfd · outbound

This paper cites URL https://developers.google.com/ optimization/cp/cp solver.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets URL https://developers.google.com/ optimization/cp/cp solver

Reference 44

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raw_fallback, observed 2026-08-15T21:00:42.783965Z

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source=pdf_text observed=2026-08-15T21:00:41.085639Z digest=sha256:456176366296829caa875ace42e216781cd03e78a252d3d6f07daf3aa75679dc

Observation 824c1753-92a7-4fec-a796-6476112f3d43 · outbound

This paper cites an unresolved cited work.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Unresolved cited work

Reference 45

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source=pdf_text observed=2026-08-15T21:00:41.088780Z digest=sha256:869ad74b5cc73dde4da35b967eb0f5fb7935fb7102011110276a314987727095

Observation c7fe74c2-c15c-4c51-86b8-513b803392c7 · outbound

This paper cites Springer series in operations research, Springer, New York, NY, USA, https://doi.org/10.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Springer series in operations research, Springer, New York, NY, USA, https://doi.org/10

Reference 46

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source=pdf_text observed=2026-08-15T21:00:41.091806Z digest=sha256:ca5e19652182209f645c787cf152fd6cf17c06c9908e83f6506a54a3e94423e0

Observation 9a00203f-1dd7-4dc6-8383-5953571341be · outbound

This paper cites Springer US, New York, NY, USA, https://doi.org/10.1007/978-3-031-05921-6.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Springer US, New York, NY, USA, https://doi.org/10.1007/978-3-031-05921-6

Reference 47

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source=pdf_text observed=2026-08-15T21:00:41.094732Z digest=sha256:c557fd13b7b2fdfcbe54ee6f8565c411fcc8415d583d14a7bcdb8cda9f4a7cec

Observation 08eacaeb-9a7c-4719-802d-8ae012e15024 · outbound

This paper cites J Intell Manuf 34(3):1311–1324.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets J Intell Manuf 34(3):1311–1324

Reference 48

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Observation f3de4a40-f64d-45e1-95f5-9bf49ce140fb · outbound

This paper cites Evolution Strategies as a Scalable Alternative to Reinforcement Learning.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Evolution Strategies as a Scalable Alternative to Reinforcement Learning

Reference 49

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Observation 06d2a2f3-6dcd-4c5c-a32c-e6840c772e94 · outbound

This paper cites URL https://simpy.readthedocs.io/en/ latest/.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets URL https://simpy.readthedocs.io/en/ latest/

Reference 50

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Observation f35dc4d4-9f97-4b87-a508-5019c2374d45 · outbound

This paper cites In: ICML, JMLR Workshop and Conference Proceedings, vol 37.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets In: ICML, JMLR Workshop and Conference Proceedings, vol 37

Reference 51

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Reference 52

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Observation fc3816dc-63ff-445b-b814-6251d4e98ec0 · outbound

This paper cites In: 2024 5th International Conference on Electronic Communication and Artificial Intelligence (ICECAI), pp 713–716, https://doi.org/10.1109/ICECAI62591.2024.10675000.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets In: 2024 5th International Conference on Electronic Communication and Artificial Intelligence (ICECAI), pp 713–716, https://doi.org/10.1109/ICECAI62591.2024.10675000

Reference 53

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source=pdf_text observed=2026-08-15T21:00:41.113805Z digest=sha256:53533ef94e6384fd6d713b8f142063b81e8af7a932ce966ca2ed4f5ac2aaae04

Observation 7050a907-8966-43c0-8f59-d76f90217adf · outbound

This paper cites IEEE Access 8:106542– 106553.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets IEEE Access 8:106542– 106553

Reference 54

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Reference 55

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doi, observed 2026-08-15T21:00:41.243515Z

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Observation 875c0486-497a-4f69-bbb7-39c82372893d · outbound

This paper cites CIRP Annals 67(1):511 – 514.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets CIRP Annals 67(1):511 – 514

Reference 57

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:00:41.126352Z digest=sha256:0afe37a955902458e61300a002031f9bba068af9bb8056359917d2a05c237855

Observation 7b863966-70f0-4b8b-96cc-ff7e31b834bb · outbound

This paper cites Adap- tive Computation and Machine Learning Series, Massachusetts Institute of Technology Press, Cambridge, Massachusetts.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Adap- tive Computation and Machine Learning Series, Massachusetts Institute of Technology Press, Cambridge, Massachusetts

Reference 58

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source=pdf_text observed=2026-08-15T21:00:41.129504Z digest=sha256:18ca0dd3301444bde5e565078537ef0188434d685afa944ef92984ff3b0fa143

Observation d2727760-e44f-4472-a740-13d3215f5c63 · outbound

This paper cites Eur J Oper Res 64(2):278–285.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Eur J Oper Res 64(2):278–285

Reference 59

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Observation 9660a99f-e735-441d-999d-6da87ea80218 · outbound

This paper cites A Reinforcement Learning Environment For Job-Shop Scheduling.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets A Reinforcement Learning Environment For Job-Shop Scheduling

Reference 60

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source=pdf_text observed=2026-08-15T21:00:41.135999Z digest=sha256:1156b3c06c8f5de5fa725a01a09b816edb60dbf8b51bf8010e863389283c63c0

Observation 94c4db51-8c65-4c7e-aca7-c92a057d98be · outbound

This paper cites an unresolved cited work.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Unresolved cited work

Reference 61

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source=pdf_text observed=2026-08-15T21:00:41.139450Z digest=sha256:a03309a54ca4f499cc7f4f91ac4717e975ff7450feae4876dcb48d9ac7c059f9

Observation 1abf5265-7e23-4437-a7b7-9f310bd87522 · outbound

This paper cites In: NIPS, pp 5998–6008.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets In: NIPS, pp 5998–6008

Reference 62

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raw_fallback, observed 2026-08-15T21:00:42.715685Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:00:41.142389Z digest=sha256:083c37952dd5a8a73245c0b7ea0d142b98c69bd0051142feefb967ce162448fa

Observation f0cfe941-c7f4-44e1-8e78-2d060a7bf98c · outbound

This paper cites In: Proceedings of International Conference on Computers and Industrial Engineering, CIE.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets In: Proceedings of International Conference on Computers and Industrial Engineering, CIE

Reference 63

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raw_fallback, observed 2026-08-15T21:00:42.704327Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:00:41.145596Z digest=sha256:75cba2763a1c3d7709302da858c5e0f487dfb1619c44378d32010b4afd0ccf99

Observation 7d48d827-d586-4611-8cbe-ce5a17894e10 · outbound

This paper cites Int J Prod Res 63(8):2871–2888.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Int J Prod Res 63(8):2871–2888

Reference 64

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Reference 65

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raw_fallback, observed 2026-08-15T21:00:41.655860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:00:41.151727Z digest=sha256:b24e3966fd235552e14c7f9d0189562110423b5fb2504933f45f39b46ff87ba4

Observation 1955845c-4637-4c3e-a0c2-ec121294ea7f · outbound

This paper cites Procedia CIRP 72:1264–.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Procedia CIRP 72:1264–

Reference 66

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raw_fallback, observed 2026-08-15T21:00:42.693130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:00:41.155066Z digest=sha256:aa0d91715ad4496daa76c0115da59ad978633cc64f6668025b934a8654f13ec3

Observation 3ba0885a-1fe7-4724-acec-1f996f392cca · outbound

This paper cites MIS Q 26(2).

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets MIS Q 26(2)

Reference 67

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raw_fallback, observed 2026-08-15T21:00:42.682319Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 7594f46c-4460-40f1-af02-d17633c0b54f · outbound

This paper cites Expert Syst Appl 35(1-2):485–496.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Expert Syst Appl 35(1-2):485–496

Reference 68

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doi, observed 2026-08-15T21:00:41.218147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:00:41.163897Z digest=sha256:d849d93273265f61d96b5d75cba2b16e7882b2db11c73a5993d732c70dd28a14

Observation 0ca4207e-abab-4596-a845-326e7b96d09b · outbound

This paper cites J Intell Manuf 31 23(6):2255–2270.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets J Intell Manuf 31 23(6):2255–2270

Reference 69

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doi, observed 2026-08-15T21:00:41.208373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:00:41.166915Z digest=sha256:4fe83a489523c21d6c375d7da9f300c587527cfcc8ae9ae6810670130b3f26d4

Observation c9df19f7-d3d6-4e7e-8ec2-b072e6f853c1 · outbound

This paper cites https://doi.org/10.1109/ NABIC.2009.5393690.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets https://doi.org/10.1109/ NABIC.2009.5393690

Reference 70

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raw_fallback, observed 2026-08-15T21:00:41.586377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:00:41.169988Z digest=sha256:d0bdb91dfde57498a5e46fc05c45a5de38a43db8b16fc4a37707bc8a00ccb104

Observation 925f9d4b-15dd-4f0b-8ac9-d7927a586fe5 · outbound

This paper cites an unresolved cited work.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Unresolved cited work

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Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets In: NeurIPS, pp 11960–11970

Reference 72

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Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Comput Ind Eng 193:110259

Reference 73

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This paper cites an unresolved cited work.

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Unresolved cited work

Reference 531

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Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Unresolved cited work

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Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets Unresolved cited work

Reference 6675

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Pith citing papers

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