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Mathematical Problems in Engineering
Volume 2013 (2013), Article ID 956978, 14 pages
http://dx.doi.org/10.1155/2013/956978
Research Article

A Fuzzy-Neural Ensemble and Geometric Rule Fusion Approach for Scheduling a Wafer Fabrication Factory

1Department of Industrial Engineering and Management, Chaoyang University of Science and Technology, Taiwan
2Department of Industrial Engineering and Systems Management, Feng Chia University, Taiwan

Received 22 March 2013; Accepted 13 June 2013

Academic Editor: Pedro Ponce

Copyright © 2013 Hsin-Chieh Wu and Toly Chen. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

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.