Group Decision-making Model Based On Rough Set And Genetic Algorithm

Decision-making is prevalent in the management activities, it can solve the curren t or future problems to select the best solution, and it's the core of the management act ivities. Group decision-making will produce large amounts of data, and these data are imprecise and non-quantitative. Traditional group decision-making in determining the decision-making results often use the experience of decision makers to reduce the effi ciency and quality of decision-making.In the process of real group decision-making, decision-makers who involve in th e decision-making process are more than one, so it will produce a large number of dec ision-making factor data. This paper combines rough set theory and genetic algorithm theory, exert their director. Rough set theory is good at dealing with imprecise knowle dge and can pre-process the data to mine a large number of implicit decision-making patterns in the data influence decision-making results. Genetic Algorithm attributes re duction, produce discriminate library, set a quantitative way to improve the quality of decision-making scientifically and reasonably.In this paper, the main research work are as follows:1. Integrating the rough set theory and the theory of genetic algorithms into e ach of the group decision-making process, and construct an integrated grou p decision-making model based on rough sets and genetic algorithm.2. Pre-processing the information that is generated by the group decision usin g rough set theory, propose a feature extraction scheme of four decision fa ctors in group decision-making process.3. Using the genetic algorithm to make attributes simple in the group decisio n-making model.4. Introducing a group decision-making case as to an information constructio n in a company, and having a test to validate the model.