灰關聯分析的加權TOPSIS法在餐飲業服務評價中的應用

A synthetic evaluation of Food Service based on Grey Correlation and weight TOPSIS method

為提高餐飲業服務評估的客觀性與科學性，將灰色系統理論引入理想解法中，構造一種新的貼近度指標，判定品質的等級及優劣排序，避免了理想解法在遇到貼近度相等時不能區分樣本之間優劣性的情況，使得評估更加合理。此外，以灰靶貢獻度理論為依據，提供一套權重的求解方法，並給出了求解公式．用貢獻度理論求得各指標的貢獻度，並求其均值；以各指標的貢獻度與均值的差為參考，確定相應指標的權與權均值的差，並以此為依據建立權值的求解公式，求得相應指標的權．實現了權重的主客觀統一，為評估奠定基礎。實例分析表明，該方法能細化餐飲業服務品質的等級，使得評價結果更加客觀、合理和全面。在實際應用中，這套處理複雜問題的程式是非常方便容易；根據這種方法得出的結論有利於業者對評估進行綜合管理和運用，證明該方法的簡便性和有效性。

In order to evaluate the coffee service quality objectively and scientifically, a novel relative similarity degree index is presented to evaluate the grade of food service quality and order preference by integrating the grey correlation analysis into the ideal solution (TOPSIS) method. Then it can avoid the case that TOPSIS cannot distinguish samples' disparity due to the equal relative similarity degrees. Furthermore, according to the theory of grey target contribution degree, a method of solving weights is proposed with the formula of solving weights derived. First, the contributing degree of indices and their mean can be solved by means of the theory of contribution degree; Secondly, the deviation of weights from the mean of these weights is determined according to the deviation of contributing degree of indices from the mean of contributing degree. Based on this, the formula of solving weights can be derived. A case study demonstrates that the proposed method can elaborate the grade of food service and make the food service assessment being more objective, reasonable and comprehensive. Finally, an example is used to illustrate the validity and simplicity of the method.