2-tuple Linguistic Fuzzy Stochastic MAGDM Method Based on Prospect Theory and Cloud Model

DOI

10.2991/itim-17.2017.40How to use a DOI?

Keywords

Prospect theory, multi-attributes group decision-making, Cloud model, 2-tuple linguistic

Abstract

This paper presents a new approach to solving the fuzzy stochastic multi attributes group decision-making (MAGDM) problem where the attributes values take 2-tuple linguistic form. First, a 2-tuple hybrid ordered weighted geometric (THOWG) operator is developed and all the individual preference values are aggregated into the comprehensive preference values. Then, by applying generating cloud method, a comprehensive preference value is converted into a normal cloud. Consequently, the cloud prospect decision matrix is constructed by defining a cloud distance, cloud possibility degree and cloud prospect value function. Furthermore, we establish a programming model which satisfies maximum integrated cloud prospect value, attain the attributes weights, and consequently list the order of alternatives. Finally, an example is illustrated to verify the developed approach.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xiaorui Li
PY  - 2017/08
DA  - 2017/08
TI  - 2-tuple Linguistic Fuzzy Stochastic MAGDM Method Based on Prospect Theory and Cloud Model
BT  - Proceedings of the 2017 International Conference on Information Technology and Intelligent Manufacturing (ITIM 2017)
PB  - Atlantis Press
SP  - 162
EP  - 171
SN  - 1951-6851
UR  - https://doi.org/10.2991/itim-17.2017.40
DO  - 10.2991/itim-17.2017.40
ID  - Li2017/08
ER  -