Reducing inconsistency in pairwise comparisons using multi-objective evolutionary computing

Edward Abel; Ludmil Mikhailov; John Keane

doi:10.1109/SMC.2013.21

Reducing inconsistency in pairwise comparisons using multi-objective evolutionary computing

Edward Abel, Ludmil Mikhailov, John Keane

Software Systems

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

Abstract

Pairwise comparisons are commonly used to estimate values of preference among a finite set of decision alternatives with regards to intangible factors. Inconsistency within decision making judgments may occur. This work proposes an approach to reducing inconsistency using multi-objective optimization with the objectives of different inconsistency types and judgment modification measures. The approach allows the decision maker to choose both the inconsistency measure(s) and the modification measure(s) employed to suit their needs and attitudes. Utilizing multi-objective optimization allows for a range of possible tradeoff solutions to be presented to the decision maker for selection, aiding them in their pursuit of inconsistency reduction. It also enables better understanding of the characteristics of the decision problem and its inconsistency.

Original language	English
Title of host publication	2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013, Manchester
Place of Publication	Piscataway
Publisher	IEEE
Pages	80-85
Number of pages	6
ISBN (Print)	9780769551548
DOIs	https://doi.org/10.1109/SMC.2013.21
Publication status	Published - 2013
Event	IEEE International Conference on Systems, Man, and Cybernetics - Manchester, United Kingdom Duration: 13 Oct 2013 → 16 Oct 2013

Conference

Conference	IEEE International Conference on Systems, Man, and Cybernetics
Country/Territory	United Kingdom
City	Manchester
Period	13/10/13 → 16/10/13

Keywords

Decision analysis
Evolutionary computing
Genetic algorithmns
Inconsistency
Multi-objective optimiszation

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10.1109/SMC.2013.21

Cite this

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title = "Reducing inconsistency in pairwise comparisons using multi-objective evolutionary computing",

abstract = "Pairwise comparisons are commonly used to estimate values of preference among a finite set of decision alternatives with regards to intangible factors. Inconsistency within decision making judgments may occur. This work proposes an approach to reducing inconsistency using multi-objective optimization with the objectives of different inconsistency types and judgment modification measures. The approach allows the decision maker to choose both the inconsistency measure(s) and the modification measure(s) employed to suit their needs and attitudes. Utilizing multi-objective optimization allows for a range of possible tradeoff solutions to be presented to the decision maker for selection, aiding them in their pursuit of inconsistency reduction. It also enables better understanding of the characteristics of the decision problem and its inconsistency.",

keywords = "Decision analysis, Evolutionary computing, Genetic algorithmns, Inconsistency, Multi-objective optimiszation",

author = "Edward Abel and Ludmil Mikhailov and John Keane",

year = "2013",

doi = "10.1109/SMC.2013.21",

language = "English",

isbn = "9780769551548",

pages = "80--85",

booktitle = "2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013, Manchester",

publisher = "IEEE",

address = "United States",

note = "IEEE International Conference on Systems, Man, and Cybernetics ; Conference date: 13-10-2013 Through 16-10-2013",

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Abel, E, Mikhailov, L & Keane, J 2013, Reducing inconsistency in pairwise comparisons using multi-objective evolutionary computing. in 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013, Manchester., 6721774, IEEE, Piscataway, pp. 80-85, IEEE International Conference on Systems, Man, and Cybernetics, Manchester, United Kingdom, 13/10/13. https://doi.org/10.1109/SMC.2013.21

Reducing inconsistency in pairwise comparisons using multi-objective evolutionary computing. / Abel, Edward; Mikhailov, Ludmil; Keane, John.
2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013, Manchester. Piscataway: IEEE, 2013. p. 80-85 6721774.

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

TY - GEN

T1 - Reducing inconsistency in pairwise comparisons using multi-objective evolutionary computing

AU - Abel, Edward

AU - Mikhailov, Ludmil

AU - Keane, John

PY - 2013

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N2 - Pairwise comparisons are commonly used to estimate values of preference among a finite set of decision alternatives with regards to intangible factors. Inconsistency within decision making judgments may occur. This work proposes an approach to reducing inconsistency using multi-objective optimization with the objectives of different inconsistency types and judgment modification measures. The approach allows the decision maker to choose both the inconsistency measure(s) and the modification measure(s) employed to suit their needs and attitudes. Utilizing multi-objective optimization allows for a range of possible tradeoff solutions to be presented to the decision maker for selection, aiding them in their pursuit of inconsistency reduction. It also enables better understanding of the characteristics of the decision problem and its inconsistency.

AB - Pairwise comparisons are commonly used to estimate values of preference among a finite set of decision alternatives with regards to intangible factors. Inconsistency within decision making judgments may occur. This work proposes an approach to reducing inconsistency using multi-objective optimization with the objectives of different inconsistency types and judgment modification measures. The approach allows the decision maker to choose both the inconsistency measure(s) and the modification measure(s) employed to suit their needs and attitudes. Utilizing multi-objective optimization allows for a range of possible tradeoff solutions to be presented to the decision maker for selection, aiding them in their pursuit of inconsistency reduction. It also enables better understanding of the characteristics of the decision problem and its inconsistency.

KW - Decision analysis

KW - Evolutionary computing

KW - Genetic algorithmns

KW - Inconsistency

KW - Multi-objective optimiszation

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DO - 10.1109/SMC.2013.21

M3 - Conference contribution

AN - SCOPUS:84893548690

SN - 9780769551548

SP - 80

EP - 85

BT - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013, Manchester

PB - IEEE

CY - Piscataway

T2 - IEEE International Conference on Systems, Man, and Cybernetics

Y2 - 13 October 2013 through 16 October 2013

ER -

Reducing inconsistency in pairwise comparisons using multi-objective evolutionary computing

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Keywords

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