Evolving fuzzy rules for due-date assignment problem in semiconductor manufacturing factory
Evolving fuzzy rules for due-date assignment problem in semiconductor manufacturing factory
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DOI：
10.1007/s10845-005-1663-4
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发表时间：
2005-10
影响因子：
8.3
通讯作者：
P. Chang;Jih-Chang Hieh;T. Warren Liao
中科院分区：
文献类型：
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作者：
P. Chang;Jih-Chang Hieh;T. Warren Liao
本文介绍了Wang和Mendel提出的一种模糊建模方法，该方法利用仿真模型产生的数据来生成模糊规则，该模型来自台湾新竹科技园的一个实际工厂。该模糊建模方法是用遗传算法对制造业中的交货期分配问题进行了进一步的进化。通过仿真数据验证了该方法的有效性，并与其他两种软计算技术：多层感知器神经网络和基于案例的推理方法进行了比较。比较结果表明，本文提出的方法始终优于其他两种方法。
This paper presents a fuzzy modeling method proposed by Wang and Mendel for generation of fuzzy rules using data generated from a simulated model that is built from a real factory located in Hsin-Chu science-based park of Taiwan, R.O.C. The fuzzy modeling method is further evolved by a genetic algorithm for due-date assignment problem in manufacturing. By using simulated data, the effectiveness of the proposed method is shown and compared with two other soft computing techniques: multi-layer perceptron neural networks and case-based reasoning. The comparative results indicate that the proposed method is consistently superior to the other two methods.