A decision model for making decisions under epistemic uncertainty and its application to select materials. Issue 3 (3rd August 2017)

• Record Type: Journal Article
• Authors: Shahinur, Sweety; Ullah, A.M.M. Sharif; Noor-E-Alam, Muhammad; Haniu, Hiroyuki; Kubo, Akihiko
• Editors: Ghanem, Roger; Du, Xiaoping
• Is Part Of: AI EDAM. Volume 31:Issue 3(2017)
• Page Start: 298
• Page End: 312
• Publication Date: 2017-08-03
• Subjects: Decision Making, -- Engineering Design, -- Epistemic Uncertainty, -- Material Selection; Engineering design -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; 620.00420285
• DOI: 10.1017/S0890060417000191
• Languages: English
• ISSNs: 0890-0604

Abstract

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.