关键词: 多准则决策, 分类, 二次偏好聚合函数, 不完全信息

Abstract: To improve the existing methods for multi-criteria classification decision-making problems, a nonlinear hierarchical discrimination approach was presented for multi-criteria classification decision-making problems under correlated criteria and incomplete information. In this method, the whole decision process for classifying the alternatives to corresponding group was accomplished by the form of hierarchy. For each class, the first step was to build the multi-criteria classification optimization model through reference set and preference relationship. Then the optimization model would be achieved by algorithms based on evolutionary strategy and annealing penalty function. After that the coefficients of preference aggregation function and other parameters could be obtained, and the consistence index computation was conducted so as to discriminate and confirm the right class for each alternative. At last, scientific and reasonable results of a practical example have demonstrated that this approach was feasible, effective and close to the real situation.

Key words: multi-criteria decision making, classification, quadratic preference aggregation function, incomplete information