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

Authors:
R. K. Singh;A. K. Choudhury;M. K. Tiwari;R. Shankar
Affiliations:
Department of Production Engineering, Birla Institute of Technology Mesra, Ranchi 835 215, India;Sustainable Design Laboratory, 101 Engineering Management Department, 1870 Miner Circle, UMR, Rolla, MO 65409, USA;Department of Forge Technology, National Institute of Foundry and Forge Technology, Hatia, Ranchi 834 003, India;Department of Management Studies, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110 016, India
Venue:
Advanced Engineering Informatics
Year:
2007

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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.