Automatic design of scheduling rules for complex manufacturing systems by multi-objective simulation-based optimization
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- @Article{Freitag:2016:AMT,
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author = "Michael Freitag and Torsten Hildebrandt",
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title = "Automatic design of scheduling rules for complex
manufacturing systems by multi-objective
simulation-based optimization",
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journal = "\{CIRP\} Annals - Manufacturing Technology",
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volume = "65",
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number = "1",
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pages = "433--436",
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year = "2016",
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ISSN = "0007-8506",
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DOI = "doi:10.1016/j.cirp.2016.04.066",
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URL = "http://www.sciencedirect.com/science/article/pii/S000785061630066X",
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abstract = "Complex manufacturing systems pose challenges for
production planning and control. Amongst other
objectives, orders have to be finished according to
their due-dates. However, avoiding both earliness and
tardiness requires a high level of process control.
This article describes the use of simulation-based
multi-objective optimization (multi-objective Genetic
Programming) as a hyper-heuristic to automatically
develop improved dispatching rules specifically for
this control problem. Using a complex manufacturing
scenario from semiconductor manufacturing as an
example, it is shown that the resulting rules
significantly outperform state-of-the-art dispatching
rules from literature.",
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keywords = "genetic algorithms, genetic programming, Manufacturing
systems, Scheduling, Hyper-heuristic",
- }
Genetic Programming entries for
Michael Freitag
Torsten Hildebrandt
Citations