Application Research On Rough Set Theory To Multi-Attribute Decision Making

With the advancement and development of the society, the research and application in decision-making methods have greatly improved. But information society coming today, the decisioin problems we face are becoming more and more complicated. For example: the coexistence of dynamic quality and static quality; the coexistence of single target and multiple targets(critera), and so on. Among the multi-criteria decision problems, multi-attribute decision-making problem need meet the following some strict hypothesis:(1) the attribute sets should be compeleted, it reflects all important aspects of the decision problem;(2) the attribute value should be calculated, so it can be used to do further analysis;(3) the attribute set should be composed into several parts, so simplify the further evaluation process;(4) the attribute set should be non-redundancy, which means all attributes have no intersection;(5)the attribute set should be minimization. And as well the classic decision making methods depend on the decision maker's experience strongly. But it is impossible to meet the above requirements under the mass information happening environment, and we hope we make any decision objectively, but not subjectively. So, it's urgent to provide a suit of decision methods which can dispose objectively decision problems with weak constraints.Based on great searching for internal and external information and following closely international advanced technology, we deeply analyzes the characteristic of the complex decision and introduce international advanced thoughts and methods such as rought sets theory into classical multi-attribute decision methods; at the same time many kinds of scientific knowledge for example management, artificial intelligence, informatics and so on are melted well. In the systematic point of view, we make emphases to research rough sets attribute reduction theory, rough set classification,S-rough set's application to the classic multi-attribute decision making problems, considering the the strict hypothesizes; furthermore we put forward a set of multi-attribute decision methods based on rough set theory. Finally using some example for calculating, simulation and experiment, we prove this set of method has the theory value and...