- author = "Torsten Hildebrandt and Debkalpa Goswami and Michael Freitag",
- booktitle = "Winter Simulation Conference (WSC 2014)",
- title = "Large-scale simulation-based optimization of semiconductor dispatching rules",
- year = "2014",
- month = dec,
- pages = "2580--2590",
- keywords = "genetic algorithms, genetic programming, MIMAC FAB6",
-
DOI = "
doi:10.1109/WSC.2014.7020102",
- size = "11 pages",
- abstract = "Developing dispatching rules for complex production systems such as semiconductor manufacturing is an involved task usually performed manually. In a tedious trial-and-error process, a human expert attempts to improve existing rules, which are evaluated using discrete-event simulation. A significant improvement in this task can be achieved by coupling a discrete-event simulator with heuristic optimisation algorithms. In this paper we show that this approach is feasible for large manufacturing scenarios as well, and it is also useful to quantify the value of information for the scheduling process. Using the objective of minimising the mean cycle time of lots, we show that rules created automatically using Genetic Programming (GP) can clearly outperform standard rules. We compare their performance to manually developed rules from the literature.",
-
notes = "BIBA-Bremer Inst. fur Produktion und Logistik GmbH at
the ArcelorMittal Bremen, Univ. Bremen, Bremen,
Germany
Also known as \cite{7020102}",
