PSS Evaluation Based on Vague Assessment Big Data: Hybrid Model of Multi-Weight Combination and Improved TOPSIS by Relative Entropy
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초록
Driven by the vague assessment big data, a product service system (PSS) evaluation method is developed basedon a hybrid model of multi-weight combination and improved TOPSIS by relative entropy. The index valuesof PSS alternatives are solved by the integration of the stakeholders’ vague assessment comments presented inthe form of trapezoidal fuzzy numbers. Multi-weight combination method is proposed for index weight solvingof PSS evaluation decision-making. An improved TOPSIS by relative entropy (RE) is presented to overcomethe shortcomings of traditional TOPSIS and related modified TOPSIS and then PSS alternatives are evaluated. A PSS evaluation case in a printer company is given to test and verify the proposed model. The RE closenessof seven PSS alternatives are 0.3940, 0.5147, 0.7913, 0.3719, 0.2403, 0.4959, and 0.6332 and the one with thehighest RE closeness is selected as the best alternative. The results of comparison examples show that thepresented model can compensate for the shortcomings of existing traditional methods.
Abstract
Driven by the vague assessment big data, a product service system (PSS) evaluation method is developed basedon a hybrid model of multi-weight combination and improved TOPSIS by relative entropy. The index valuesof PSS alternatives are solved by the integration of the stakeholders’ vague assessment comments presented inthe form of trapezoidal fuzzy numbers. Multi-weight combination method is proposed for index weight solvingof PSS evaluation decision-making. An improved TOPSIS by relative entropy (RE) is presented to overcomethe shortcomings of traditional TOPSIS and related modified TOPSIS and then PSS alternatives are evaluated. A PSS evaluation case in a printer company is given to test and verify the proposed model. The RE closenessof seven PSS alternatives are 0.3940, 0.5147, 0.7913, 0.3719, 0.2403, 0.4959, and 0.6332 and the one with thehighest RE closeness is selected as the best alternative. The results of comparison examples show that thepresented model can compensate for the shortcomings of existing traditional methods.
참고문헌 (15)
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