دانلود رایگان مقاله مدل طرح ریزی فازی ناخوشایند برای تصمیم گیری چند معیاره برای سیستم های پشتیبانی تصمیم گیری بیمارستان

Abstract

To improve the ability and efficiency of the hospital management, it is needed for us to handle the decision making problems so as to assist the hospital decision support systems. Considering the complexity and urgency of the hospital management affairs, this paper proposes a projection model with hesitant fuzzy linguistic term sets to solve the decision making problems under consideration. The proposed model not only can describe the uncertainties of the problems and the hesitancy of the decision makers, but also can decrease subjective and increase objectives of the decision making results. Then, the error analysis method is provided to obtain the weights of the criteria with hesitant fuzzy linguistic information. Furthermore, we make comparisons between the proposed model and other decision making methods, and present its advantages and drawbacks. Finally, a case study on hospital decision support systems is made to illustrate the validity and applicability of the proposed model.

6. Conclusions

To improve the hospital management efficiency, this paper has proposed a hesitant fuzzy linguistic fuzzy projection model to handle the decision-making problems in the HDSS, which considers the characteristics of the medical management, such as uncertainty, complexity, urgency, and so on. Since the decision-making problems in HDSS are various and the factors are polytropic, the paper has proposed the error analysis method to determine the priority vector of the factors. Later on, some discussions have been provided for the proposed model, including comparing it with other decision-making methods, assessing its advantages and drawbacks. Last but not least, the paper has applied the proposed model to select the optimal medicine purchase project. The obtained results have been approved by the hospital experts as the best prescription in drug procurement plans, which manifests that the proposed model has strong applicability and effectiveness to deal with the problems in HDSS. In general, the proposed method not only can process the decision-making problems with all original hesitant fuzzy linguistic information, but also can obtain the decision results straightforwardly and conveniently. In addition, according to the comparative analyses with other MCDM methods, we can easily find that if we only consider the distance of two vectors and ignore their direction, we will lose some important decision information. From this point of view, the proposed model gives a valid way to handle the decision matrix.