Using data mining to find patterns in genetic algorithm solutions to a job shop schedule
Computers and Industrial Engineering
Self-Organizing Maps
Applying a Fuzzy and Neural Approach for Forecasting the Foreign Exchange Rate
International Journal of Fuzzy System Applications
Applied Computational Intelligence and Soft Computing - Special issue on Applied Neural Intelligence to Modeling, Control, and Management of Human Systems and Environments
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The production system of a wafer fabrication factory is a very complicated process. Job scheduling in a wafer fabrication factory is a very difficult task. To solve this problem, two intelligent scheduling rules are proposed in this study. The intelligent scheduling rules are modified from the well-known fluctuation smoothing rules with some innovative treatments. To evaluate the effectiveness of the proposed methodology, production simulation was also applied in this study. According to experimental results, the proposed methodology outperformed some existing approaches by reducing the average cycle time and cycle time standard deviation, the most important objectives of job scheduling in a wafer fabrication factory.