A HYBRID DYNAMIC MADM MODEL FOR PROBLEM-IMPROVEMENT IN ECONOMICS AND BUSINESS

Abstract

A typical multiple attribute decision making (MADM) model is a scientific analytical model for evaluating and improving a set of alternatives based on multiple criteria. However, this study identified some important new concepts and limitations/defects of traditional MADM for solving the real-world problems. First, the traditional MADM model assumes that criteria considered are independent and hierarchical in structure; however, the real-world problems often involve interdependent criteria, and thus interdependent models are required. Second, relatively good solutions from existing alternatives are replaced by the aspiration levels. Third, the trend has shifted from how to "rank"or "select" the most preferable alternatives, to how to "improve" their performances. Fourth, information fusion/aggregation, such as fuzzy integrals, basically, a non-additive/super-additive model, has been developed for performance aggregation. Therefore, to overcome the defects of the conventional MADM method and solve complex and dynamic real world problems, a Hybrid Dynamic Multiple Criteria Decision Making (HDMADM) method is needed. Finally, this study presented real cases to demonstrate the effectiveness of the HDMADM method for overcoming the defects of the conventional MADM method.