A hybrid approach to determining the best combination on product form design

Authors:
Yang-Cheng Lin;Hsin-Hsi Lai;Chung-Hsing Yeh;Chen-Hui Hung
Affiliations:
Department of Industrial Design, National Cheng Kung University, Tainan, Taiwan;Department of Industrial Design, National Cheng Kung University, Tainan, Taiwan;School of Business Systems, Monash University, Clayton, Victoria, Australia;Department of Chinese Literature, National Cheng Kung University, Tainan, Taiwan
Venue:
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part IV
Year:
2005

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Abstract

This paper presents a hybrid approach, using a grey relational analysis (GRA), neural networks (NNs), and a tabu search (TS) algorithm, to determining the best combination of product form design. The GRA model is used to identify the most influential elements of product form. The NN model is used in conjunction with the GRA model, in order to predict and suggest the best form design combination. The TS is applied to search for the best global solution. The hybrid approach provides useful insights to help product designers work out the best combination of product form design for matching the given product image.