Minimizing Deviations Models for Solving MADM Problems with Preference Information on Alternatives in Uncertain Linguistic Setting
نویسنده
چکیده
In this paper, we investigate the multiple attribute decision making (MADM) in uncertain linguistic setting where the information about attribute weights is incompletely known and the attribute values are uncertain linguistic variables, and the decision maker (DM) has preferences on alternatives. We establish two optimization models, which minimize deviations between the overall attribute values of alternatives and the overall preference values. Based on these two models and a formula of possibility degree for the comparison between uncertain linguistic variables, we propose a method for MADM with preference information on alternatives in uncertain linguistic setting. The method can sufficiently meet the DM’s requirements and can also be performed on computer easily. Finally, we apply the method to evaluate university faculty for tenure and promotion. KeywordsMultiple attribute decision making (MADM), Uncertain linguistic variables, Model, Deviation, Preference ∗ Corresponding author’s email: [email protected] 1813-713X copyright © 2006 ORSTW International Journal of Operations Research
منابع مشابه
Interval MULTIMOORA method with target values of attributes based on interval distance and preference degree: biomaterials selection
A target-based MADM method covers beneficial and non-beneficial attributes besides target values for some attributes. Such techniques are considered as the comprehensive forms of MADM approaches. Target-based MADM methods can also be used in traditional decision-making problems in which beneficial and non-beneficial attributes only exist. In many practical selection problems, some attributes ha...
متن کاملExtension of the TODIM Method to Intuitionistic Linguistic Multiple Attribute Decision Making
Practical decision situations are becoming increasingly complicated. It is common for a person to select or rank alternatives with respect to multiple attributes, and the TODIM (an acronym in Portuguese of interactive and multiple attribute decision making) method, which is one of the first multiple attribute decision making (MADM) methods based on prospect theory, has received more attention d...
متن کاملA New Balancing and Ranking Method based on Hesitant Fuzzy Sets for Solving Decision-making Problems under Uncertainty
The purpose of this paper is to extend a new balancing and ranking method to handle uncertainty for a multiple attribute analysis under a hesitant fuzzy environment. The presented hesitant fuzzy balancing and ranking (HF-BR) method does not require attributes’ weights through the process of multiple attribute decision making (MADM) under hesitant conditions. For the rating of possible alternati...
متن کاملSensitivity Analysis of TOPSIS Technique: The Results of Change in the Weight of One Attribute on the Final Ranking of Alternatives
Most of data in Multi-attribute decision making (MADM) problems are changeable rather than constant and stable. Therefore, sensitivity analysis after problem solving can effectively contribute to making accurate decisions. In this paper, we offer a new method for sensitivity analysis in multi-attribute decision making problems in which if the weights of one attribute changes, then we can dete...
متن کاملA Subjective and Objective Integrated Approach to Multiple Attribute Decision Making with Preference Information on Alternatives
This paper investigates the multiple attribute decision making (MADM) problems with preference information on alternatives. An integrated approach is proposed to solve the MADM problems, where decision makers' subjective preference information on alternatives are given in different formats, uniformed and aggregated. The resulting social subjective preference information on the alternatives is i...
متن کامل