Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/195613
Authors: 
Sharaf, Iman Mohamad
Year of Publication: 
2018
Citation: 
[Journal:] Journal of Industrial Engineering International [ISSN:] 2251-712X [Volume:] 14 [Year:] 2018 [Issue:] 2 [Pages:] 383-394
Abstract: 
The choice of suitable robots in manufacturing, to improve product quality and to increase productivity, is a complicated decision due to the increase in robot manufacturers and configurations. In this article, a novel approach is proposed to choose among alternatives, differently assessed by decision makers on different criteria, to make the final evaluation for decision-making. The approach is based on the ellipsoid algorithm for systems of linear inequalities. Most of the ranking methods depend on integration that becomes complicated for nonlinear membership functions, which is the case in robot selection. The method simply uses the membership function or its derivative. It takes the decision maker's attitude in ranking. It effectively ranks fuzzy numbers and their images, preserving symmetry. It is a simple recursive algebraic formula that can be easily programmed. The performance of the algorithm is compared with the performance of some existing methods through several numerical examples to illustrate its advantages in ranking, and a robot selection problem is solved.
Subjects: 
Fuzzy multicriteria decision-making
Ranking fuzzy numbers
The ellipsoid method
Robot selection
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by/4.0/
Document Type: 
Article

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