The evidential reasoning approach for multi-attribute decision analysis under both fuzzy and interval uncertainty

Min Guo; Jian Bo Yang; Kwai Sang Chin; Hongwei Wang

doi:10.1007/978-3-540-77664-2_11

The evidential reasoning approach for multi-attribute decision analysis under both fuzzy and interval uncertainty

Min Guo, Jian Bo Yang, Kwai Sang Chin, Hongwei Wang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Many multiple attribute decision analysis (MADA) problems are characterised 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 evidential reasoning (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 FIER approach, local ignorance and grade fuzziness are modelled 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. © 2008 Springer-Verlag Berlin Heidelberg.

Original language	English
Title of host publication	Advances in Soft Computing\|Adv. Soft Comput.
Pages	129-140
Number of pages	11
Volume	46
DOIs	https://doi.org/10.1007/978-3-540-77664-2_11
Publication status	Published - 2008
Event	International Workshop on Interval and Probabilistic Uncertainty in Knowledge Representation and Decision Making - JAIST, Nomi, Japan Duration: 25 Mar 2008 → 28 Mar 2008

Conference

Conference	International Workshop on Interval and Probabilistic Uncertainty in Knowledge Representation and Decision Making
City	JAIST, Nomi, Japan
Period	25/03/08 → 28/03/08

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10.1007/978-3-540-77664-2_11

Cite this

@inproceedings{51df07e6a5534a2a906c5d18b7ea209e,

title = "The evidential reasoning approach for multi-attribute decision analysis under both fuzzy and interval uncertainty",

abstract = "Many multiple attribute decision analysis (MADA) problems are characterised 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 evidential reasoning (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 FIER approach, local ignorance and grade fuzziness are modelled 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} 2008 Springer-Verlag Berlin Heidelberg.",

author = "Min Guo and Yang, {Jian Bo} and Chin, {Kwai Sang} and Hongwei Wang",

year = "2008",

doi = "10.1007/978-3-540-77664-2_11",

language = "English",

isbn = "9783540776635",

volume = "46",

pages = "129--140",

booktitle = "Advances in Soft Computing|Adv. Soft Comput.",

note = "International Workshop on Interval and Probabilistic Uncertainty in Knowledge Representation and Decision Making ; Conference date: 25-03-2008 Through 28-03-2008",

}

Guo, M, Yang, JB, Chin, KS & Wang, H 2008, The evidential reasoning approach for multi-attribute decision analysis under both fuzzy and interval uncertainty. in Advances in Soft Computing|Adv. Soft Comput.. vol. 46, pp. 129-140, International Workshop on Interval and Probabilistic Uncertainty in Knowledge Representation and Decision Making, JAIST, Nomi, Japan, 25/03/08. https://doi.org/10.1007/978-3-540-77664-2_11

TY - GEN

T1 - The evidential reasoning approach for multi-attribute decision analysis under both fuzzy and interval uncertainty

AU - Guo, Min

AU - Yang, Jian Bo

AU - Chin, Kwai Sang

AU - Wang, Hongwei

PY - 2008

Y1 - 2008

N2 - Many multiple attribute decision analysis (MADA) problems are characterised 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 evidential reasoning (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 FIER approach, local ignorance and grade fuzziness are modelled 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. © 2008 Springer-Verlag Berlin Heidelberg.

AB - Many multiple attribute decision analysis (MADA) problems are characterised 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 evidential reasoning (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 FIER approach, local ignorance and grade fuzziness are modelled 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. © 2008 Springer-Verlag Berlin Heidelberg.

U2 - 10.1007/978-3-540-77664-2_11

DO - 10.1007/978-3-540-77664-2_11

M3 - Conference contribution

SN - 9783540776635

VL - 46

SP - 129

EP - 140

BT - Advances in Soft Computing|Adv. Soft Comput.

T2 - International Workshop on Interval and Probabilistic Uncertainty in Knowledge Representation and Decision Making

Y2 - 25 March 2008 through 28 March 2008

ER -

The evidential reasoning approach for multi-attribute decision analysis under both fuzzy and interval uncertainty

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