A fuzzy rule for improving the performance of multiobjective job dispatching in a wafer fabrication factory

This paper proposes a fuzzy slack-diversifying fluctuation-smoothing rule to enhance the scheduling performance in a wafer fabrication factory. the proposed rule considers the uncertainty in the remaining cycle time and is aimed at simultaneous improvement of the average cycle time,cycle time standard deviation,the maximum lateness,and number of tardy jobs. existing publications rarely discusse ways to optimize all of these at the same time. an important input to the proposed rule is the job remaining cycle time. to this end,this paper proposes a self-adjusted fuzzy back propagation network (sa-fbpn) approach to estimate the remaining cycle time of a job. in addition,a systematic procedure is also established,which can solve the problem of slack overlapping in a nonsubjective way and optimize the overall scheduling performance. the simulation study provides evidence that the proposed rule can improve the four performance measures simultaneously. © 2013 toly chen and yi-chi wang.