A Neural Network Model for the Decision-Making Process Based on ANP
Satoshi Matsuda · The 2006 IEEE International Joint Conference on Neural Network Proceedings · 2006
Many attempts have been made to develop neural network models of the intellectual activities of human beings. However, to our knowledge few attempts have been made to develop a neural network model of the process of decisionmaking, which is a typical intellectual activity. In this paper we propose a neural network model of the decision-making process based on the analytic network process by T. L. Saaty (2001). Although we, S. Matsuda (2005) previously proposed a neural network model for the decision-making process based on the analytic hierarchy process by T. L. Saaty (1972), the analytic network process is more elaborate than the analytic hierarchy process. By viewing decision making as an optimization process based on the analytic network process to satisfy many objectives to the greatest degree possible, we present a neural network model of the decision-making process. Furthermore, the model also works effectively in more practical situations where we cannot give the precise information or all the information necessary to make the decision. Finally, we apply the proposed neural network to an example and illustrate its validity through simulations.