Lagrange-enhanced GRA method for probabilistic simplified neutrosophic MADM: Yaozhou porcelain decoration design quality evaluation

Abstract

Yaozhou ware is located in Huangbao Town, Tongchuan City. It began in the Song Dynasty and flourished in the Tang Dynasty. Its warm and jade like glaze color, exquisite decorative techniques, and rich and varied utensil shapes all give it a very important position in history. The traditional Yaozhou porcelain contains the ancient people’s concept of creation and their attitude towards humans and nature. Each artifact of Yaozhou porcelain contains the designer’s understanding and emotions about the world, establishing a dialogue between people and objects to form a desired lifestyle. The production method of Yaozhou porcelain that has been preserved for thousands of years shares many similarities with modern design ideas. The quality evaluation of Yaozhou porcelain decoration design is viewed as multiple-attribute decision-making (MADM). The grey relational analysis (GRA) is a useful tool to cope with the MADM issue. The probabilistic simplified Neutrosophic set (PSNSs) is easy to characterize uncertain information during the quality evaluation of Yaozhou porcelain decoration design. In this paper, in order to obtain the weight information, an optimization model is constructed to obtain a simple and exact formula which can be employed to derive the attribute weights values based on the Lagrange function and the probabilistic simplified neutrosophic (PSN) grey relational analysis (PSN-GRA) method is originated for MADM to rank the decision alternatives. Finally, a numerical example for quality evaluation of Yaozhou porcelain decoration design is used to verify the practicability of the PSN-GRA method and compares it with other methods.