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Neural Computing and Applications

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01.12.2013 | Original Article

A fuzzy-neural approach for supporting three-objective job scheduling in a wafer fabrication factory

verfasst von: Toly Chen, Yu-Cheng Wang

Erschienen in: Neural Computing and Applications | Sonderheft 1/2013

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Abstract

This study is dedicated to three-objective scheduling in a wafer fabrication factory, which has rarely been discussed in the literature but is a very important task. Optimizing a single objective in a complex production system like a wafer fabrication factory is already quite complicated. Optimizing three objectives at the same time is obviously even more complicated. To this end, this study presents a fuzzy-neural approach that fuses three existing rules in a nonlinear way, and which can be tailored, and even optimized, for a wafer fabrication factory. To assess the effectiveness of the proposed methodology, production simulation is also applied in this study. According to the experimental results, the proposed methodology is better than some existing approaches in reducing the average cycle time, the maximum lateness, and cycle time standard deviation.

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Titel: A fuzzy-neural approach for supporting three-objective job scheduling in a wafer fabrication factory
verfasst von: Toly Chen
Yu-Cheng Wang
Publikationsdatum: 01.12.2013
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe Sonderheft 1/2013
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-013-1460-5

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