Neuro-Fuzzy Approximation of Multi-Criteria Decision-Making QFD Methodology

Ajith Abraham, Pandian Vasant and Arijit Bhattacharya
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Ajith Abraham: Norwegian University of Science and Technology
Pandian Vasant: Universiti Teknologi Petronas
Arijit Bhattacharya: Dublin City University, Glasnevin

A chapter in Fuzzy Multi-Criteria Decision Making, 2008, pp 301-321 from Springer

Abstract: Abstract This chapter demonstrates how a neuro-fuzzy approach could produce outputs of a further-modified multi-criteria decision-making (MCDM) quality function deployment (QFD) model within the required error rate. The improved fuzzified MCDM model uses the modified S-curve membership function (MF) as stated in an earlier chapter. The smooth and flexible logistic membership function (MF) finds out fuzziness patterns in disparate level-of-satisfaction for the integrated analytic hierarchy process (AHP-QFD model. The key objective of this chapter is to guide decision makers in finding out the best candidate-alternative robot with a higher degree of satisfaction and with a lesser degree of fuzziness.

Keywords: ANFIS; AHP; QFD; fuzziness patterns; decision-making; level-of-satisfaction (search for similar items in EconPapers)
Date: 2008
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DOI: 10.1007/978-0-387-76813-7_12

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