International Journal of Computational Intelligence Systems

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Volume 12, Issue 2, 2019, Pages 1179 - 1196

Aggregating Interrelated Attributes in Multi-Attribute Decision-Making With ELICIT Information Based on Bonferroni Mean and Its Variants

Authors
Bapi Dutta1, Álvaro Labella2, *, Rosa M. Rodríguez2, Luis Martínez2
1The Logistics Institute Asia Pacific, National University of Singapore, 21 Heng Mui Keng Terrace, Singapore, 119613, Singapore
2Department of Computer Science, University of Jaén, Campus Las Lagunillas, Jaén, 23071, Spain
*Corresponding author. Email: alabella@ujaen.es
Corresponding Author
Álvaro Labella
Received 27 August 2019, Accepted 28 September 2019, Available Online 21 October 2019.
DOI
10.2991/ijcis.d.190930.002How to use a DOI?
Keywords
ELICIT information; Aggregation operator; Interrelationship; Bonferroni mean
Abstract

In recent times, to improve the interpretability and accuracy of computing with words processes, a rich linguistic representation model has been developed and referred to as Extended Comparative Linguistic Expressions with Symbolic Translation (ELICIT). This model extends the definition of the comparative linguistic expressions into a continuous domain due to the use of the symbolic translation concept related to the 2-tuple linguistic model. The aggregation of ELICIT information via a suitable rule that reflects the underlying interrelation among the aggregated information in output is the key tool to design decision-making algorithm for solving multi-attribute decision-making problems under linguistic information. In this study, we introduce three aggregation operators for aggregating ELICIT information in aim of capturing three different types of interrelationship patterns among inputs, which we refer to as ELICIT Bonferroni mean, ELICIT extended Bonferroni mean and ELICIT partitioned Bonferroni mean. Further, the key aggregation properties of these proposed operators are investigated with the proposal of weighted forms. Based on the proposed aggregation operators, an approach for solving multi-attribute decision-making problems, in which attributes are interrelated is developed. Finally, a didactic example is presented to illustrate the working of the proposal and demonstrate its feasibility.

Copyright
© 2019 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
12 - 2
Pages
1179 - 1196
Publication Date
2019/10/21
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.2991/ijcis.d.190930.002How to use a DOI?
Copyright
© 2019 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

risenwbib
TY  - JOUR
AU  - Bapi Dutta
AU  - Álvaro Labella
AU  - Rosa M. Rodríguez
AU  - Luis Martínez
PY  - 2019
DA  - 2019/10/21
TI  - Aggregating Interrelated Attributes in Multi-Attribute Decision-Making With ELICIT Information Based on Bonferroni Mean and Its Variants
JO  - International Journal of Computational Intelligence Systems
SP  - 1179
EP  - 1196
VL  - 12
IS  - 2
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.190930.002
DO  - 10.2991/ijcis.d.190930.002
ID  - Dutta2019
ER  -