Evidential reasoning approach for multiattribute decision analysis under both fuzzy and Interval uncertainty

Min Guo; Jian-Bo Yang; Kwai-Sang Chin; Hong-Wei Wang; Xin-Bao Liu

doi:10.1109/TFUZZ.2008.928599

Evidential reasoning approach for multiattribute decision analysis under both fuzzy and Interval uncertainty

Min Guo
, Jian-Bo Yang
, Kwai-Sang Chin
, Hong-Wei Wang
, Xin-Bao Liu

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

81 Citations (Scopus)

Abstract

Many multiple attribute decision analysis (MADA) problems are characterized by both quantitative and qualitative attributes with various types of uncertainties. Incompleteness (or ignorance) and vagueness (or fuzziness) are among the most common uncertainties in decision analysis. The evidential reasoning (ER) and the interval grade ER (IER) approaches have been developed in recent years to support the solution of MADA problems with interval uncertainties and local ignorance in decision analysis. In this paper, the ER approach is enhanced to deal with both interval uncertainty and fuzzy beliefs in assessing alternatives on an attribute. In this newly developed fuzzy IER (FIER) approach, local ignorance and grade fuzziness are modeled under the integrated framework of a distributed fuzzy belief structure, leading to a fuzzy belief decision matrix. A numerical example is provided to illustrate the detailed implementation process of the FIER approach and its validity and applicability. © 2009 IEEE.

Original language	English
Pages (from-to)	683-697
Journal	IEEE Transactions on Fuzzy Systems
Volume	17
Issue number	3
DOIs	https://doi.org/10.1109/TFUZZ.2008.928599
Publication status	Published - 2009

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Research Keywords

Aggregates
Algorithm design and analysis
Analytical models
Artificial neural networks
Business
Cognition
Customer satisfaction
Data models
Equations
Evidential reasoning (ER) approach
Facsimile
Fuzzy set theory
Fuzzy sets
Image processing
Intelligent control
Laboratories
Manufacturing
Marine vehicles
Mathematical model
Modeling
Multiple attribute decision analysis
Multiple attribute decision analysis (MADA)
Numerical models
Periodic structures
Research and development management
Safety
Shape
Software safety
Synthetic aperture radar
The evidential reasoning approach
Uncertainty
Uncertainty modeling
Utility
Utility theory

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title = "Evidential reasoning approach for multiattribute decision analysis under both fuzzy and Interval uncertainty",

abstract = "Many multiple attribute decision analysis (MADA) problems are characterized by both quantitative and qualitative attributes with various types of uncertainties. Incompleteness (or ignorance) and vagueness (or fuzziness) are among the most common uncertainties in decision analysis. The evidential reasoning (ER) and the interval grade ER (IER) approaches have been developed in recent years to support the solution of MADA problems with interval uncertainties and local ignorance in decision analysis. In this paper, the ER approach is enhanced to deal with both interval uncertainty and fuzzy beliefs in assessing alternatives on an attribute. In this newly developed fuzzy IER (FIER) approach, local ignorance and grade fuzziness are modeled under the integrated framework of a distributed fuzzy belief structure, leading to a fuzzy belief decision matrix. A numerical example is provided to illustrate the detailed implementation process of the FIER approach and its validity and applicability. {\textcopyright} 2009 IEEE.",

keywords = "Aggregates, Algorithm design and analysis, Analytical models, Artificial neural networks, Business, Cognition, Customer satisfaction, Data models, Equations, Evidential reasoning (ER) approach, Facsimile, Fuzzy set theory, Fuzzy sets, Image processing, Intelligent control, Laboratories, Manufacturing, Marine vehicles, Mathematical model, Modeling, Multiple attribute decision analysis, Multiple attribute decision analysis (MADA), Numerical models, Periodic structures, Research and development management, Safety, Shape, Software safety, Synthetic aperture radar, The evidential reasoning approach, Uncertainty, Uncertainty modeling, Utility, Utility theory",

author = "Min Guo and Jian-Bo Yang and Kwai-Sang Chin and Hong-Wei Wang and Xin-Bao Liu",

year = "2009",

doi = "10.1109/TFUZZ.2008.928599",

language = "English",

volume = "17",

pages = "683--697",

journal = "IEEE Transactions on Fuzzy Systems",

issn = "1063-6706",

publisher = "IEEE",

number = "3",

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TY - JOUR

T1 - Evidential reasoning approach for multiattribute decision analysis under both fuzzy and Interval uncertainty

AU - Guo, Min

AU - Yang, Jian-Bo

AU - Chin, Kwai-Sang

AU - Wang, Hong-Wei

AU - Liu, Xin-Bao

PY - 2009

Y1 - 2009

N2 - Many multiple attribute decision analysis (MADA) problems are characterized by both quantitative and qualitative attributes with various types of uncertainties. Incompleteness (or ignorance) and vagueness (or fuzziness) are among the most common uncertainties in decision analysis. The evidential reasoning (ER) and the interval grade ER (IER) approaches have been developed in recent years to support the solution of MADA problems with interval uncertainties and local ignorance in decision analysis. In this paper, the ER approach is enhanced to deal with both interval uncertainty and fuzzy beliefs in assessing alternatives on an attribute. In this newly developed fuzzy IER (FIER) approach, local ignorance and grade fuzziness are modeled under the integrated framework of a distributed fuzzy belief structure, leading to a fuzzy belief decision matrix. A numerical example is provided to illustrate the detailed implementation process of the FIER approach and its validity and applicability. © 2009 IEEE.

AB - Many multiple attribute decision analysis (MADA) problems are characterized by both quantitative and qualitative attributes with various types of uncertainties. Incompleteness (or ignorance) and vagueness (or fuzziness) are among the most common uncertainties in decision analysis. The evidential reasoning (ER) and the interval grade ER (IER) approaches have been developed in recent years to support the solution of MADA problems with interval uncertainties and local ignorance in decision analysis. In this paper, the ER approach is enhanced to deal with both interval uncertainty and fuzzy beliefs in assessing alternatives on an attribute. In this newly developed fuzzy IER (FIER) approach, local ignorance and grade fuzziness are modeled under the integrated framework of a distributed fuzzy belief structure, leading to a fuzzy belief decision matrix. A numerical example is provided to illustrate the detailed implementation process of the FIER approach and its validity and applicability. © 2009 IEEE.

KW - Aggregates

KW - Algorithm design and analysis

KW - Analytical models

KW - Artificial neural networks

KW - Business

KW - Cognition

KW - Customer satisfaction

KW - Data models

KW - Equations

KW - Evidential reasoning (ER) approach

KW - Facsimile

KW - Fuzzy set theory

KW - Fuzzy sets

KW - Image processing

KW - Intelligent control

KW - Laboratories

KW - Manufacturing

KW - Marine vehicles

KW - Mathematical model

KW - Modeling

KW - Multiple attribute decision analysis

KW - Multiple attribute decision analysis (MADA)

KW - Numerical models

KW - Periodic structures

KW - Research and development management

KW - Safety

KW - Shape

KW - Software safety

KW - Synthetic aperture radar

KW - The evidential reasoning approach

KW - Uncertainty

KW - Uncertainty modeling

KW - Utility

KW - Utility theory

UR - https://www.scopus.com/pages/publications/67149120771

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-67149120771&origin=recordpage

U2 - 10.1109/TFUZZ.2008.928599

DO - 10.1109/TFUZZ.2008.928599

M3 - RGC 21 - Publication in refereed journal

SN - 1063-6706

VL - 17

SP - 683

EP - 697

JO - IEEE Transactions on Fuzzy Systems

JF - IEEE Transactions on Fuzzy Systems

IS - 3

ER -

Evidential reasoning approach for multiattribute decision analysis under both fuzzy and Interval uncertainty

Abstract

UN SDGs

Research Keywords

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