Research On Muti-objective Optiminzation Design Of Productf Under Genetic Factor Theory

In a market saturated with fierce competition, commodities which cannot meet the psychological expectations of consumers will eventually be eliminated. At the same time, due to the continuous progress and development of science and technology, various disciplines cross each other and learn from each other, which is leading to a high degree of integration between different disciplines. In this context, the biological survival of the fittest is extended to the field of industrial design, main focuses of which are how to give the product a unique form and style image, to improve the public recognition, and to shape the brand under the current trend of technology homogenization. On the other hand, consumers' preferences for product shape design have an important impact on the purchase decision so companies should take individual preference into account when designing the product. At present, the product development and design is mainly based on qualitative research,which mainly relies on the perceptual experience and intuitive understanding of designers and lacks of quantitative and accurate analysis and research.In this paper, the Kansei Engineering and genetic algorithm were applied to multi-objective evolutionary modeling process of the product, which included the research of theory and application and focused on the application of the method. It mainly included the following four parts. The first part consisted of the knowledge framework of product gene,Kansei Engineering and product image design. In the second part, the author analyzed and determined the technical methods of the multi objective image of the product, took the TREK mountain bike frame as an example and used the multidimensional scaling analysis method and SPSS software to determine the target image adjective pairs of the four groups of products.The third part was made up of using the analytic hierarchy process experiment and cluster analysis method to determine the representative sample and draw the diagram,while positioning coordinates of each representative sample of other movements of each key point value as parameters of sample. In the fourth part, multi objective evolutionary based on genetic algorithm was used for frame modeling and the evolution result was investigated and analyzed on the platform of Matlab 2014a GUI. It was concluded that the overall process and technical methods in this essay were feasible.The research of multi objective optimization design of product modeling is helpful to design the product modeling based on the improvement of the brand product identification. At the same time,it also provides a valuable theoretical reference for the development of future product modeling genes.