Improved Decision Neural Network (IDNN) based consensus method to solve a multi-objective group decision making problem

Abstract

Multi-criterion frameworks involving several subjective and quantitative factors that allow the complexity of Group Decision Making (GDM) to get worsen, especially for those problems which are having strategic dimensions. Recently, integration of multi-attribute utility theory (MAUT) and feed-forward neural network have been studied with a view to facilitate the automation of GDM. In this paper Improved Decision Neural Network (IDNN) based methodology has been developed to solve the multi-criterion decision problem in GDM. Reductions in the training data set, exploitation of indirect methods like multiplicative preference relation during the training process, and reduced number of iterations to map the MAUF are the advantages of this novel methodology. In this research, a soft consensus based group decision making methodology under linguistic assessments have been adopted for consensus forming among the groups.