標題: Optimization of parameter design: an intelligent approach using neural network and simulated annealing
作者: Su, CT
Chang, HH
工業工程與管理學系
Department of Industrial Engineering and Management
公開日期: 1-十二月-2000
摘要: Parameter design optimization problems have found extensive industrial applications, including product development, process design and operational condition setting. The parameter design optimization problems are complex because non-lineal relationships and interactions may occur among parameters. To resolve such problems, engineers commonly employ the Taguchi method. However, the Taguchi method has some limitations in practice. Therefore, in this work, we present a novel means of improving the effectiveness of the optimization of parameter design. The proposed approach employs the neural network and simulated annealing, and consists of two phases. Phase I formulates an objective function for a problem using a neural network method to predict the value of the response for a given parameter setting. Phase 2 applies the simulated annealing algorithm to search for the optimal parameter combination. A numerical example demonstrates the effectiveness of the proposed approach.
URI: http://dx.doi.org/10.1080/00207720050217313
http://hdl.handle.net/11536/30088
ISSN: 0020-7721
DOI: 10.1080/00207720050217313
期刊: INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
Volume: 31
Issue: 12
起始頁: 1543
結束頁: 1549
顯示於類別:期刊論文


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  1. 000166013000003.pdf