An interactive approach to select optimal solution for MADM problems with preferential dependence

The ‘optimal’ solution for a decision making problem should be the one that best reflects the decision-maker’s preference. For MADM (Multi-Attribute Decision-Making) problems, however, finding an optimal solution is difficult, especially when the number of alternatives, or that of attributes is relatively large. Most of the existing mathematical approches arrive at a final solution on the basis of many unrealistic assumptions, without reflecting the decision-maker’s preference structure exactly. To remedy this, some interactive methods have been proposed, but most of them require a large amount of information growing exponentially as the number of alternatives, or that of attributes increases. Therefore it is difficult for the decision-maker to maintain consistency throughout the decision making process. In this paper, an interactive method which finds optimal solutions for deterministic MADM problems with many attributes and alternatives is proposed. Instead of considering all the attributes simultaneously, this method partitions all the attributes into several mutually independent subgroups and considers one of them at each of preordered steps, where the alternatives are eliminated until the optimal one is obtained. The efficiency of the method lies in the fact that the amount of necessary information is reduced significantly, and even further if a suboptimal solution is acceptable to the decision-maker. [In Korean.]