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A decision model for making decisions under epistemic uncertainty and its application to select materials

Published online by Cambridge University Press:  03 August 2017

Sweety Shahinur ,
A.M.M. Sharif Ullah ,
Muhammad Noor-E-Alam ,
Hiroyuki Haniu  and
Akihiko Kubo
Sweety Shahinur
Affiliation:
Graduate School of Engineering, Kitami Institute of Technology, Kitami, Hokkaido, Japan
A.M.M. Sharif Ullah*
Affiliation:
Department of Mechanical Engineering, Kitami Institute of Technology, Kitami, Hokkaido, Japan
Muhammad Noor-E-Alam
Affiliation:
Department of Mechanical and Industrial Engineering, Northeastern University, Boston, Massachusetts, USA
Hiroyuki Haniu
Affiliation:
Department of Mechanical Engineering, Kitami Institute of Technology, Kitami, Hokkaido, Japan
Akihiko Kubo
Affiliation:
Department of Mechanical Engineering, Kitami Institute of Technology, Kitami, Hokkaido, Japan
*
Reprint requests to: A.M.M. Sharif Ullah, Department of Mechanical Engineering, Kitami Institute of Technology, 165 Koen-cho, Kitami, Hokkaido 090-8507, Japan. E-mail: ullah@mail.kitami-it.ac.jp
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Abstract

This study deals with both a decision model for making decisions under epistemic uncertainty and how to use it for selecting optimal materials under the same uncertainty. In particular, the proposed decision model employs a set of possibilistic objective functions defined by fuzzy numbers to handle a set of conflicting criteria. In addition, the model can calculate the compliance of a piece of decision-relevant (imprecise) information with a given objective function. Moreover, the model is capable to aggregate the calculated compliances for the sake of ranking a given set of alternatives against the set of conflicting criteria. The problem of selecting materials for making the body of a vehicle is considered as an example. In this problem, the indices for selecting the materials are unknown because the specifications regarding the vehicle body are not given. In addition, the data relevant to material properties entails a great deal of imprecision. The presented decision model can quantify the above-mentioned epistemic uncertainty in a lucid manner and generate a list of optimal materials.

Keywords

Decision MakingEngineering DesignEpistemic UncertaintyMaterial Selection
Type
Special Issue Articles
Information
AI EDAM , Volume 31 , Special Issue 3: Uncertainty Quantification for Engineering Design , August 2017 , pp. 298 - 312
Copyright
Copyright © Cambridge University Press 2017 

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