An Approach to Evaluate the Clothing Creative Design with Dual Hesitant Fuzzy Information

Theproblemof evaluating the clothing creative designwith dual hesitant fuzzy information is themultiple attribute decisionmaking problem. In this paper, we have utilized dual hesitant fuzzy hybrid average (DHFHA) operator to develop the model to solve the multiple attribute decision making problems for evaluating the clothing creative design. Finally, a practical example for evaluating the clothing creative design is given to verify the developed approach.


Introduction
In the context of innovation-driven reformation and development of fashion industry in China, it becomes the most essential issue to enhance the ability of independent R&D and creative design level for Chinese local fashion brands.In quite a long period, fashion is considered to be determined by fashion designers [1,2].However, fashion is hereby considered to be formed according to certain social background, instead of being determined by certain people's subjective minds.So fashion could be generated by precise analysis from objective factors.Now in the context of fast fashion, fashion design does not merely rely on the designers' creativity, but all kinds of modern information technology are applied in the process of fashion design [3][4][5].According to the characteristics of the fashion data warehouse system, an overall structure composed of fashion data dictionary, fashion data sources, fashion data management, fashion data mining, and the front-end decision support is formed.The proposed concept of Fashion Data Dictionary (FDD), including Fashion Color Data Dictionary, Fashion Material Data Dictionary, Fashion Accessory Data Dictionary, Fashion Pattern Data Dictionary, Fashion Technique Data Dictionary, Fashion Style Data Dictionary, and Fashion Look Data Dictionary, is formed, in order that all kinds of fashion data from different sources are unified in format.Each data dictionary regulates its data type, level, content, and standard presentation [6,7].Sources of fashion data extraction are fashion clothing, social background, and art works.Fashion clothing data sources include fashion shows, fashion market, fashion brand advertisement, target consumer, fashion e-shop, and fashion and fabric exhibition.Social background data sources include politics, economy, environment, science and technology, sports, and lifestyle.Art works data sources include TV drama, art, design, music, performance art, and literature [8].The fashion data management is defined including fashion data extraction, naming method, conversion rules, and loading standard, so that the fashion data extracted from a variety of sources could be loaded in the fashion warehouse with standardized data format.Social background has an important impact on the formation of fashion style which is the consensus of the fashion industry, but the study of the relationship between the two has always been to stay in the sociology of qualitative research [9][10][11].
The problem of evaluating the clothing creative design with dual hesitant fuzzy information is the multiple attribute decision making problems.In this paper, we have utilized dual hesitant fuzzy hybrid average (DHFHA) operator to develop the model to solve the multiple attribute decision making problems for evaluating the clothing creative design.Finally, a practical example for evaluating the evaluating the clothing creative design is given to verify the developed approach.
In the following, Wang et al. [13] had developed some dual hesitant fuzzy arithmetic aggregation operator based on the operations of DHFEs.
In the following, we apply the DHFHA operator to the MADM problems for evaluating the clothing creative design with dual hesitant fuzzy information.

Numerical Example
Thus, in this section we will present a numerical example for evaluating the clothing creative design with dual hesitant fuzzy information in order to illustrate the method proposed in this paper.There are five possible clothing creative design alternatives   ( = 1, 2, 3, 4, 5) for four attributes   ( = 1, 2, 3, 4).The four attributes include the fashion design style ( 1 ), the color of dress design ( 2 ), the fabrics of clothing design ( 3 ), and the design of comfort ( 4 ), respectively.In order to avoid influencing each other, the decision makers are required to evaluate five possible clothing creative design alternatives   ( = 1, 2, 3, 4, 5) under the above four attributes in anonymity and the decision matrix D = ( d ) 5×4 is presented in Table 1.
In the following, we utilize the approach developed for evaluating the clothing creative design with dual hesitant fuzzy information.

Conclusion
In this paper, we have utilized dual hesitant fuzzy hybrid average (DHFHA) operator to develop the model to solve the multiple attribute decision making problems for evaluating the clothing creative design.Finally, a practical example for evaluating the clothing creative design is given to verify the developed approach.