DESIGNING A MULTIPLE ATTRIBUTE DECISION MAKING PROBLEM WITH FUZZY DATA

ABSTRACT

Multiple Attribute Decision Making (MADM) problems are commonly encountered in everyday aspect of life. They aim at selecting the optimal alternative among some courses of action in the presence of multiple, usually conflicting, attributes. It is not surprising that, at times, the performance rating cannot be assessed precisely. It may be represent the subjectivity and/or imprecision in human behavior. A remedial means for modeling such uncertainty is the utilization of fuzzy data. Differing from the existing studies in the area of fuzzy MADM, the main purpose of this paper is concerned with the problem of how to efficiently select the optimal alternative for an MADM problem with fuzzy data, where the decision-maker's preference information (i.e., the attributes' weights) is completely known. First, an intuitively appealing selection rule is proposed. Next, under a minimum probability of correct selection of the proposed selection rule, the optimal design (i.e., the number of the values of attributes for each alternative) is obtained by minimizing the total cost of collecting data. A numerical example is provided to illustrate the proposed method.

Keywords:

• multiple attribute decision making
• weights
• minimal probability of correct selection
• optimal design