Abstract
In this paper, a new data mining tool which is called TACO-miner is used to determine composite Dispatching Rules (DR) under a given set of shop parameters (i.e., interarrival times, pre-shop pool length). The main purpose is to determine a set of composite DRs which are a combination of conventional DRs (i.e., FIFO, SPT). In or-der to achieve this, full factorial experiments are carried out to determine the effect of input parameters on predetermined performance measures. Afterwards, the data set which is obtained from the full factorial simulation analyses is feed into the TACO-miner in order to determine composite DRs. The preliminary verification study has shown that composite DRs have an acceptable performance.
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Baykasoğlu, A., Göçken, M., Özbakır, L., Kulluk, S. (2008). Composite Dispatching Rule Generation through Data Mining in a Simulated Job Shop. In: Le Thi, H.A., Bouvry, P., Pham Dinh, T. (eds) Modelling, Computation and Optimization in Information Systems and Management Sciences. MCO 2008. Communications in Computer and Information Science, vol 14. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87477-5_42
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DOI: https://doi.org/10.1007/978-3-540-87477-5_42
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