2020
DOI: 10.1007/978-3-030-62784-3_66
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A Parallel Machine Scheduling Problem for a Plastic Injection Company

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Cited by 3 publications
(3 citation statements)
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“…In this study, they consider machine constraints, transaction sequences and processing times and deadlines in multi-order situations. 2 In another study, a new approach is presented to train a machine learning-based model and includes simulation data to minimize the number of physical experiments.…”
Section: Introductionmentioning
confidence: 99%
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“…In this study, they consider machine constraints, transaction sequences and processing times and deadlines in multi-order situations. 2 In another study, a new approach is presented to train a machine learning-based model and includes simulation data to minimize the number of physical experiments.…”
Section: Introductionmentioning
confidence: 99%
“…Aslaner et al have conducted research that will help future studies on machine scheduling problems to be created by establishing mathematical modelling. In this study, they consider machine constraints, transaction sequences and processing times and deadlines in multi‐order situations 2 . In another study, a new approach is presented to train a machine learning‐based model and includes simulation data to minimize the number of physical experiments.…”
Section: Introductionmentioning
confidence: 99%
“…Aslaner et al, have done research that will help future studies for machine scheduling problems to be created by establishing a mathematical modeling in their work. In this study, they consider machine constraints, transaction sequences and processing times and deadlines in multi-order situations (Aslaner et al, 2021). In another study, a new approach is presented to train a machine learning-based model, and includes simulation data to minimize the amount of physical experiments.…”
Section: Introductionmentioning
confidence: 99%