Automatic design of scheduling rules for complex manufacturing systems by multi-objective simulation-based optimization

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@Article{Freitag:2016:AMT,

• author = "Michael Freitag and Torsten Hildebrandt",
• title = "Automatic design of scheduling rules for complex manufacturing systems by multi-objective simulation-based optimization",
• journal = "\{CIRP\} Annals - Manufacturing Technology",
• volume = "65",
• number = "1",
• pages = "433--436",
• year = "2016",
• ISSN = "0007-8506",
• DOI = "doi:10.1016/j.cirp.2016.04.066",
• URL = "http://www.sciencedirect.com/science/article/pii/S000785061630066X",
• 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.",
• keywords = "genetic algorithms, genetic programming, Manufacturing systems, Scheduling, Hyper-heuristic",

}

Genetic Programming entries for Michael Freitag Torsten Hildebrandt

Citations