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New Multi-criteria Decision-Making Based on Fuzzy Similarity, Distance and Ranking

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 565))

Abstract

We propose a new method for group decision making by using trapezoidal fuzzy numbers to describe decisions. A team of decision makers (or experts) must choose the most appropriate alternative using fuzzy logic. Each expert will give his opinion about every alternative in accordance with the criteria of choice by a fuzzy number. The decisions taken are aggregated respecting the similarity and dissimilarity (distance) between each pair of opinions, in addition to the hierarchical weights (importance) of each decision-maker (DM). The result is a fuzzy number representing the general appreciation of each alternative. In order to able to choose one, an appropriate ranking method is proposed. In this article we treat four issues, namely, similarity and distance between opinions represented by fuzzy numbers, aggregation of opinions while preserving similarity and in accordance with the hierarchical weight, and finally ranking fuzzy numbers.

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El Alaoui, M., Ben-Azza, H., Zahi, A. (2018). New Multi-criteria Decision-Making Based on Fuzzy Similarity, Distance and Ranking. In: Abraham, A., Haqiq, A., Ella Hassanien, A., Snasel, V., Alimi, A. (eds) Proceedings of the Third International Afro-European Conference for Industrial Advancement — AECIA 2016. AECIA 2016. Advances in Intelligent Systems and Computing, vol 565. Springer, Cham. https://doi.org/10.1007/978-3-319-60834-1_15

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  • DOI: https://doi.org/10.1007/978-3-319-60834-1_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60833-4

  • Online ISBN: 978-3-319-60834-1

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