A fuzzy-neural ensemble and geometric rule fusion approach for scheduling a wafer fabrication factory

Hsin Chieh Wu, Tin-Chih Chen*

*Corresponding author for this work

研究成果: Article同行評審

8 引文 斯高帕斯(Scopus)

摘要

In this study, the fuzzy-neural ensemble and geometric rule fusion approach is presented to optimize the performance of job dispatching in a wafer fabrication factory with an intelligent rule. The proposed methodology is a modification of a previous study by fusing two dispatching rules and diversifying the job slacks in novel ways. To this end, the geometric mean of the neighboring distances of slacks is maximized. In addition, the fuzzy c-means (FCM) and backpropagation network (BPN) ensemble approach was also proposed to estimate the remaining cycle time of a job, which is an important input to the new rule. A new aggregation mechanism was also designed to enhance the robustness of the FCM-BPN ensemble approach. To validate the effectiveness of the proposed methodology, some experiments have been conducted. The experimental results did support the effectiveness of the proposed methodology.

原文English
文章編號956978
期刊Mathematical Problems in Engineering
2013
DOIs
出版狀態Published - 5 八月 2013

指紋 深入研究「A fuzzy-neural ensemble and geometric rule fusion approach for scheduling a wafer fabrication factory」主題。共同形成了獨特的指紋。

引用此