Complementary Judgment Matrix Method with Imprecise Information for Multicriteria Decision-Making
Abstract
The complementary judgment matrix (CJM) method is an MCDA (multicriteria decision aiding) method based on pairwise comparisons. As in AHP, the decision-maker (DM) can specify his/her preferences using pairwise comparisons, both between different criteria and between different alternatives with respect to each criterion. The DM specifies his/her preferences by allocating two nonnegative comparison values so that their sum is 1. We measure and pinpoint possible inconsistency by inconsistency errors. We also compare the consistency of CJM and AHP trough simulation. Because preference judgments are always more or less imprecise or uncertain, we introduce a way to represent the uncertainty through stochastic distributions, and a computational method to treat the uncertainty. As in Stochastic Multicriteria Acceptability Analysis (SMAA), we consider different uncertainty levels: precise comparisons, imprecise comparisons with a stochastic distribution, and missing comparisons between criteria. We compute rank acceptability indices for the alternatives, describing the probability of an alternative to obtain a given rank considering the level of uncertainty and study the influence of the uncertainty on the SMAA-CJM results.
Main Authors
Format
Articles
Research article
Published
2018
Series
Subjects
Publication in research information system
Publisher
Hindawi Publishing Corporation
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-201810174442Use this for linking
Review status
Peer reviewed
ISSN
1024-123X
DOI
https://doi.org/10.1155/2018/3695627
Language
English
Published in
Mathematical Problems in Engineering
Citation
- Wang, H., Lahdelma, R., & Salminen, P. (2018). Complementary Judgment Matrix Method with Imprecise Information for Multicriteria Decision-Making. Mathematical Problems in Engineering, 2018, Article 3695627. https://doi.org/10.1155/2018/3695627
Copyright© 2018 Haichao Wang et al.