Study Of Multiple Attribute Decision Making Methods Based On Interval Rough Numbers

The essence of multiple attribute decision making is the known alternatives gives reasonabledecision, according to the attribute information and through the scientific method or means. Atpresent, multiple attribute decision making theory and methods are applied to many areas.Objective things are complex and changeable, human thinking is fuzzy, so decision-makinginformation is often given in the form of interval rough numbers in practical decision makingproblems. Now, for this kind of problem research is still relatively little. Research which usingpossibility degree for interval rough numbers was compared has not yet to see. This paperfocuses on the attribute values are interval rough number multiple attribute decision makingproblems for research, the main work is as follows:1. In the interval rough numbers expected value is defined on the basis of improvement, thenproposed interval rough variance is defined, and an example is given to illustrate the use ofvariance, added to the desired value of equal interval rough number ranking method.2. Added some operational laws, properties and aggregation operator of interval rough numbers.The interval rough number theory will be more perfect.3. For the multiple attribute decision making problems, which incomplete information on attributeweights and the attribute values are interval rough number. Defined interval rough possibility degreeconcept, and studied that the formula has some good properties. Based on the projection thought min-maxoptimization model is used to determine the weights of attributes. At the same time give a ranking methodbased on the possibility degree matrix interval rough number. Finally, a numerical example illustrates showthe efficiency and effectiveness of this method.4. For the multiple attribute decision making problems, which the property value and thedesign of the preference values are interval rough numbers, in order to make every decisionattribute value close the preference values. Give the optimization model to determine the weightsof attributes. Calculate the expectation value of each scheme. Give the multiple attribute decisionmaking method of interval rough numbers, with preference information on alternatives. Finally,through the examples illustrate the feasibility and effectiveness.