نتایج جستجو برای: multiple attribute decision making madm
تعداد نتایج: 1305830 فیلتر نتایج به سال:
one of the most effective tools for decline cost and time, quality improvement and consequently project performance enhancement especially in construction projects, is value engineering. there are linguistic judgments in many cases of value engineering studies in construction projects such as interior design, mechanical installations design, and etc. therefore multiple attribute decision-making...
A new method is proposed to solve the multiple attribute decision making (MADM) problems with the trapezoid fuzzy linguistic variables ( Vs TFL ) based on the trapezoid fuzzy linguistic hybrid harmonic averaging (TFLHHA ) operator. To begin with, this paper reviews the concept and operational rules of the Vs TFL , the calculation method of the possibility degree with Vs TFL , and the comparison...
In this paper, we have considered an intuitionistic fuzzy entropy with both the uncertainty and hesitancy degree of IF sets. Based on this IF entropy, a new decision-making method of a multi-attribute decision making problem (MADM) has been introduced in which attribute values are expressed with IF values. In the case of attribute weight, a case with partially known attribute weights is discuss...
With respect to multiple attribute decision making (MADM) problems in which the attribute value takes the form of intuitionistic trapezoidal fuzzy number, a new decision making analysis method is developed. Firstly, some operational laws and expected values of intuitionistic trapezoidal fuzzy numbers, and distance between two intuitionistic trapezoidal fuzzy numbers, are introduced, and the com...
In the present paper, a new entropy of order and type on Interval-Valued Intutionistic Fuzzy Sets (IVIFSs) along with their proofs of validity is proposed. It has been proved that the proposed entropy has monotonic decreasing behavior with respect to and . Further, a new algorithm for multiple attribute decision making method (MADM) has been provided using the benefit attributes and cost attrib...
In this paper, we investigate the multiple attribute decision making (MADM) problems for for evaluating the computer network security with interval-valued intuitionistic fuzzy information. To determine the attribute weights, a model based on the information entropy, by which the attribute weights can be determined, is established. We utilize the interval-valued intuitionistic fuzzy weighted ave...
The sensitivity analysis for multi-attribute decision making (MADM) problems is important for two reasons: First, the decision matrix as the source of the results of a decision problem is inaccurate because it sorts the alternatives in each criterion inaccurately. Second, the decision maker may change his opinions in a time period because of changes in the importance of the criteria and in the ...
The design of weight is one of the important parts in fuzzy decision making, as it would have a deep effect on the evaluation results. Entropy is one of the weight measure based on objective evaluation. Non--probabilistic-type entropy measures for fuzzy set and interval type-2 fuzzy sets (IT2FS) have been developed and applied to weight measure. Since the entropy for (IT2FS) for decision making...
Enterprise resource planning (ERP) systems have become important part of industries as they enable industries to make their operations and resources more efficient and integrate business data process. In order to put an ERP project successfully in service, it is necessary to select an ERP system which can meet the requirements of the industries. Thus, a decision making approach for ERP system s...
In this study, we first introduce the fuzzy sets, soft sets, fuzzy soft sets and their related properties. We then present the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) that is one of classical Multiple Attribute Decision Making (MADM) methods. We also present the Grey Relation Method. In the main part of this study, we extend the TOPSIS method on the fuzzy soft se...
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