A Validity Measure for Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using data mining to find patterns in genetic algorithm solutions to a job shop schedule
Computers and Industrial Engineering
Computers and Industrial Engineering
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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This study proposes a slack-diversifying nonlinear fluctuation smoothing rule to reduce the average cycle time in a wafer fabrication factory. The slack-diversifying nonlinear fluctuation smoothing rule is derived from the one-factor tailored nonlinear fluctuation smoothing rule for cycle time variation (1f-TNFSVCT) by dynamically maximizing the standard deviation of the slack, which has been shown to improve scheduling performance in several previous studies. The effectiveness of the proposed rule has been validated via using it with a simulated data set. Based on the findings in this research we also derived several directions that can be exploited in the future.