The rough set based multi criteria method and application

The multi-criteria decision-making problem is one of the methods that preffered and applied by the managers. Multi criteria decision making data set may include the uncertain or incomplete data, in this situation, decision is getting difficult and impossible, the suggested rough set based multi criteria decision making algorithm can able to solve this manner problem. However, in the rapidly increasing data traffic, the efficient use of existing data also brings about an important situation. The rough set concept firstly proposed by Pawlak in 1982[1] that is used as an important tool for the discovery of the necessary information by using large databases. In the case of multi-criteria decision-making problems, the concept of rough set theory is derived from the fuzzy logic approach to perform the analysis of uncertain structures. The rough set theory also has the property of being able to be used in multi-criteria decision-making problems with the rules of rule reduction and classification during the analysis of large data. Rough set theory has a structure that does not contain definite limitations, such as fuzzy sets. Therefore, the rough set approach can able to analysis of the incomplete, inadequate and ambiguous information suitable for data analysis, uses incomplete information analysis, knowledge base reduction methods during this process. Rough set theory can be used as a natural method that deals with inconsistent and incomplete information, which is the basic problem of rule extraction and classification. In this study, the basic concepts of rough set theory is given. The algorithm for solving multi-criteria decision making has been developed by considering the rough set based knowledge discovery and rough set concept. Keywords: Rough Set Theory, Multi Criteria Decision Making; Entropy