Estimation of processing time using machine learning and real factory data for optimization of parallel machine scheduling problem
Year of publication: |
2021
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Authors: | Yamashiro, Hirochika ; Nonaka, Hirofumi |
Published in: |
Operations research perspectives. - Amsterdam [u.a.] : Elsevier, ISSN 2214-7160, ZDB-ID 2821932-6. - Vol. 8.2021, Art.-No. 100196, p. 1-9
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Subject: | Machine learning | Gaussian process regression | Gradient boosted decision trees | Artificial neural networks | Identical parallel machine scheduling | Operations research | Scheduling-Verfahren | Scheduling problem | Neuronale Netze | Neural networks | Künstliche Intelligenz | Artificial intelligence | Produktionssteuerung | Production control | Theorie | Theory | Operations Research | Algorithmus | Algorithm | Durchlaufzeit | Lead time | Branch-and-Bound | Branch and Bound |
Type of publication: | Article |
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Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
Language: | English |
Other identifiers: | 10.1016/j.orp.2021.100196 [DOI] hdl:10419/246451 [Handle] |
Source: | ECONIS - Online Catalogue of the ZBW |
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