A new decision method for multi-criteria decision making with numerical values based on criteria reduction

Abstract

The work is contribution a new decision method to address the challenge (large number of criteria) in multi-criteria decision making (MCDM) problems with numerical values. This new method involves criteria reduction based on the rough set theory and the relation of criteria values (tolerance and advantage relations). Using this method and building a discrenibility matrix for numerical value MCDM problems, find useful criteria and avoid useless criteria. Then, we find a new way to obtain the weights based on the discernibility matrix when criteria weights of alternatives are completely unknown. Later, we also propose a new method to rank the alternatives according to weighted combinatorial advantage criteria values (WCACV). Finally, we use a realistic voting example to demonstrate the proposed method.