Affiliations: School of Machine Science and Engineering, Northeast Petroleum University, Daqing, Heilongjiang 163318, China
Correspondence:
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Corresponding author: Wen-Qing Liu, School of Machine Science and Engineering, Northeast Petroleum University, Daqing, Heilongjiang 163318, China. Tel./Fax: +86 459 6503339; E-mail: wenqingliu2002@sohu.com.
Abstract: In the current society where manufacturing industry is growing rapidly, products upgrading is faster in accordance with people’s needs, and therefore enterprises need to be more innovative to cope with this trend. When more researches about product innovative design are conducted around the world, there are more people focusing on the research and development of the service platform for product design. In this paper, we have developed the novel linguistic multi-attribute decision-making evaluation method for product innovation design scheme with demand preferences of customers. In the method, the two-tuple linguistic representation developed in recent years is used to aggregate the linguistic assessment information. According to the traditional ideas of technique for order preference by similarity to ideal solution (TOPSIS), the optimal alternative(s) is determined by calculating the shortest distance from the two-tuple linguistic positive ideal solution (TLPIS) and on the other side the farthest distance of the two-tuple linguistic negative ideal solution (TLNIS). The method has exact characteristic in linguistic information processing. It avoided information distortion and losing which occur formerly in the linguistic information processing. Finally, a numerical example is used to illustrate the use of the proposed method. The result shows the approach is simple, effective and easy to calculate.
Keywords: Linguistic multi-attribute decision-making, linguistic assessment information, two-tuple, TOPSIS, product innovation design scheme
