Article ID: | iaor19961343 |
Country: | Netherlands |
Volume: | 11 |
Issue: | 5 |
Start Page Number: | 415 |
End Page Number: | 429 |
Publication Date: | Jun 1994 |
Journal: | Decision Support Systems |
Authors: | Wang Jun |
Preference is an essential ingredient in all decision processes. This paper presents a new connectionist paradigm for preference assessment in a general multicriteria decision setting. A general structure of an artificial neural network for representing two specified prototypes of preference structures is discussed. An interactive preference assessment procedure and an autonomous learning algorithm based on a novel scheme of supervised learning are proposed. Operating characteristics of the proposed paradigm are also illustrated through detailed results of numerical simulations.