Multi-criteria decision analysis without consistency in pairwise comparisons
Result description
Life itself is colorful and brings situations where making the right decision is a matter of compromise given the various criteria, often conflicting with each other. To handle such situations, a plethora of mathematical methods supporting decision-making has been developed. A little attention has been paid to cases where either criteria or expert preferences are not transitive by nature. Usually, standard decision-making methods handle such a case as an input error (input inconsistency). Being designed for consistent cases, standard methods may conclude in wrong results. We present a novel framework aimed at dealing with inconsistent preferences, without forcing experts to reconsider their initial judgments thus distorting their spontaneous assessments. A simulation analysis has been led to check the methodological validity of our proposal. Specifically, by setting different consistency ranges, thousands of experiments on simulated matrices confirm that our framework represents a valid alternative to the traditional practice. The applicability of the proposed approach has been eventually demonstrated through a real-world case study focused on supply chain management of a relevant industrial problem.
Keywords
Decision-Making TheoryDecision Support SystemsAnalytic Hierarchy ProcessIntransitive PreferencesSkew-symmetric Bi-linear Representation
The result's identifiers
Result code in IS VaVaI
Alternative codes found
RIV/61384399:31160/22:00057998
Result on the web
https://www.sciencedirect.com/science/article/pii/S0360835222001590?via%3Dihub
DOI - Digital Object Identifier
Alternative languages
Result language
angličtina
Original language name
Multi-criteria decision analysis without consistency in pairwise comparisons
Original language description
Life itself is colorful and brings situations where making the right decision is a matter of compromise given the various criteria, often conflicting with each other. To handle such situations, a plethora of mathematical methods supporting decision-making has been developed. A little attention has been paid to cases where either criteria or expert preferences are not transitive by nature. Usually, standard decision-making methods handle such a case as an input error (input inconsistency). Being designed for consistent cases, standard methods may conclude in wrong results. We present a novel framework aimed at dealing with inconsistent preferences, without forcing experts to reconsider their initial judgments thus distorting their spontaneous assessments. A simulation analysis has been led to check the methodological validity of our proposal. Specifically, by setting different consistency ranges, thousands of experiments on simulated matrices confirm that our framework represents a valid alternative to the traditional practice. The applicability of the proposed approach has been eventually demonstrated through a real-world case study focused on supply chain management of a relevant industrial problem.
Czech name
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Czech description
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Classification
Type
Jimp - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
50204 - Business and management
Result continuities
Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Computers & Industrial Engineering
ISSN
0360-8352
e-ISSN
1879-0550
Volume of the periodical
168
Issue of the periodical within the volume
1
Country of publishing house
US - UNITED STATES
Number of pages
11
Pages from-to
108089
UT code for WoS article
000805828400016
EID of the result in the Scopus database
2-s2.0-85126665738
Basic information
Result type
Jimp - Article in a specialist periodical, which is included in the Web of Science database
OECD FORD
Business and management
Year of implementation
2022