A multi-attribute decision making procedure using fuzzy numbers and hybrid aggregators

The classical Analytical Hierarchy Process (AHP) has two limitations. Firstly, it disregards the aspect of uncertainty that usually embedded in the data or information expressed by human. Secondly, it ignores the aspect of interdependencies among attributes during aggregation. The application of fu...

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Main Author:	Anath Rau, Krishnan
Format:	Thesis
Language:	eng eng
Published:	2014
Subjects:	QA299.6-433 Analysis QA71-90 Instruments and machines
Online Access:	https://etd.uum.edu.my/4462/1/s92695.pdf https://etd.uum.edu.my/4462/7/s92695_abstract.pdf
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id	my-uum-etd.4462
record_format	uketd_dc
institution	Universiti Utara Malaysia
collection	UUM ETD
language	eng eng
advisor	Mat Kasim, Maznah Engku Abu Bakar, Engku Muhammad Nazri
topic	QA299.6-433 Analysis QA71-90 Instruments and machines
spellingShingle	QA299.6-433 Analysis QA71-90 Instruments and machines Anath Rau, Krishnan A multi-attribute decision making procedure using fuzzy numbers and hybrid aggregators
description	The classical Analytical Hierarchy Process (AHP) has two limitations. Firstly, it disregards the aspect of uncertainty that usually embedded in the data or information expressed by human. Secondly, it ignores the aspect of interdependencies among attributes during aggregation. The application of fuzzy numbers aids in confronting the former issue whereas, the usage of Choquet Integral operator helps in dealing with the later issue. However, the application of fuzzy numbers into multi-attribute decision making (MADM) demands some additional steps and inputs from decision maker(s). Similarly, identification of monotone measure weights prior to employing Choquet Integral requires huge number of computational steps and amount of inputs from decision makers, especially with the increasing number of attributes. Therefore, this research proposed a MADM procedure which able to reduce the number of computational steps and amount of information required from the decision makers when dealing with these two aspects simultaneously. To attain primary goal of this research, five phases were executed. First, the concept of fuzzy set theory and its application in AHP were investigated. Second, an analysis on the aggregation operators was conducted. Third, the investigation was narrowed on Choquet Integral and its associate monotone measure. Subsequently, the proposed procedure was developed with the convergence of five major components namely Factor Analysis, Fuzzy-Linguistic Estimator, Choquet Integral, Mikhailov‘s Fuzzy AHP, and Simple Weighted Average. Finally, the feasibility of the proposed procedure was verified by solving a real MADM problem where the image of three stores located in Sabak Bernam, Selangor, Malaysia was analysed from the homemakers‘ perspective. This research has a potential in motivating more decision makers to simultaneously include uncertainties in human‘s data and interdependencies among attributes when solving any MADM problems.
format	Thesis
qualification_name	Ph.D.
qualification_level	Doctorate
author	Anath Rau, Krishnan
author_facet	Anath Rau, Krishnan
author_sort	Anath Rau, Krishnan
title	A multi-attribute decision making procedure using fuzzy numbers and hybrid aggregators
title_short	A multi-attribute decision making procedure using fuzzy numbers and hybrid aggregators
title_full	A multi-attribute decision making procedure using fuzzy numbers and hybrid aggregators
title_fullStr	A multi-attribute decision making procedure using fuzzy numbers and hybrid aggregators
title_full_unstemmed	A multi-attribute decision making procedure using fuzzy numbers and hybrid aggregators
title_sort	multi-attribute decision making procedure using fuzzy numbers and hybrid aggregators
granting_institution	Universiti Utara Malaysia
granting_department	Awang Had Salleh Graduate School of Arts & Sciences
publishDate	2014
url	https://etd.uum.edu.my/4462/1/s92695.pdf https://etd.uum.edu.my/4462/7/s92695_abstract.pdf
_version_	1776103646203740160
spelling	my-uum-etd.44622023-04-02T00:43:04Z A multi-attribute decision making procedure using fuzzy numbers and hybrid aggregators 2014 Anath Rau, Krishnan Mat Kasim, Maznah Engku Abu Bakar, Engku Muhammad Nazri Awang Had Salleh Graduate School of Arts & Sciences Awang Had Salleh Graduate School of Arts and Sciences QA299.6-433 Analysis QA71-90 Instruments and machines The classical Analytical Hierarchy Process (AHP) has two limitations. Firstly, it disregards the aspect of uncertainty that usually embedded in the data or information expressed by human. Secondly, it ignores the aspect of interdependencies among attributes during aggregation. The application of fuzzy numbers aids in confronting the former issue whereas, the usage of Choquet Integral operator helps in dealing with the later issue. However, the application of fuzzy numbers into multi-attribute decision making (MADM) demands some additional steps and inputs from decision maker(s). Similarly, identification of monotone measure weights prior to employing Choquet Integral requires huge number of computational steps and amount of inputs from decision makers, especially with the increasing number of attributes. Therefore, this research proposed a MADM procedure which able to reduce the number of computational steps and amount of information required from the decision makers when dealing with these two aspects simultaneously. To attain primary goal of this research, five phases were executed. First, the concept of fuzzy set theory and its application in AHP were investigated. Second, an analysis on the aggregation operators was conducted. Third, the investigation was narrowed on Choquet Integral and its associate monotone measure. Subsequently, the proposed procedure was developed with the convergence of five major components namely Factor Analysis, Fuzzy-Linguistic Estimator, Choquet Integral, Mikhailov‘s Fuzzy AHP, and Simple Weighted Average. Finally, the feasibility of the proposed procedure was verified by solving a real MADM problem where the image of three stores located in Sabak Bernam, Selangor, Malaysia was analysed from the homemakers‘ perspective. This research has a potential in motivating more decision makers to simultaneously include uncertainties in human‘s data and interdependencies among attributes when solving any MADM problems. 2014 Thesis https://etd.uum.edu.my/4462/ https://etd.uum.edu.my/4462/1/s92695.pdf text eng public https://etd.uum.edu.my/4462/7/s92695_abstract.pdf text eng public Ph.D. doctoral Universiti Utara Malaysia Aiello, G., Enea, M., Galante, G., & La Scalia, G. (2009). Clean agent selection approached by fuzzy TOPSIS decision-making method. Fire Technology, 45(4), 405–418. Akinyele, S. T. (2010). Customer satisfaction and service quality: Customer‘s repatronage perspectives. Global Journal of Management and Business Research, 10(6). Alavi, S. H., Jassbi, J., Serra, P. J. A., & Ribeiro, R. 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