Scholarship 17/23879-9 - Processamento de sinais, Integral de Choquet - BV FAPESP
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Choquet integrals in multi-group multi-criteria decision making

Grant number: 17/23879-9
Support Opportunities:Scholarships abroad - Research Internship - Doctorate
Start date until: June 01, 2018
End date until: February 28, 2019
Field of knowledge:Engineering - Electrical Engineering
Principal Investigator:João Marcos Travassos Romano
Grantee:Guilherme Dean Pelegrina
Supervisor: Michel Grabisch
Host Institution: Faculdade de Engenharia Elétrica e de Computação (FEEC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
Institution abroad: Université Paris 1 Panthéon-Sorbonne, France  
Associated to the scholarship:16/21571-4 - Multigroup and multiple criteria decision analysis methods: models based on information processing, BP.DR

Abstract

Several practical situations can be modeled as multi-criteria decision making (MCDM) problems. Generally, methods used to deal with MCDM problems do not take into account the data structural information, such as the interaction between criteria. For example, correlated criteria may bias the decision analysis towards a specific alternative. In this context, an approach based on Choquet integrals, which can models synergy and/or redundancy between criteria, may be applied in order to consider further information about the data, avoiding biased results.Despite this method has been used to deal with several MCDM problems, there is a lack of literature in the application in a multi-group multi-criteria formulation. Therefore, a deeper understanding on the use of Choquet integrals in multi-group MCDM problems will be addressed in this research project. In this context, we aim at developing the mathematical aspects and a graphical interpretation of this formulation. Furthermore, we intent to exploit information between criteria and between decision makers in order to identify the Choquet integral parameters in both supervised and unsupervised approaches.It is worth mentioning that this internship research project lies in the context of the doctoral fellowship identified by the process number 2016/21571-4, which comprises the investigation and development of decision making methods that exploit the information found in the decision data in order to deal with multi-group and multi-criteria problems.

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Scientific publications (5)
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
PELEGRINA, GUILHERME DEAN; DUARTE, LEONARDO TOMAZELI; TRAVASSOS ROMANO, JOAO MARCOS. Application of independent component analysis and TOPSIS to deal with dependent criteria in multicriteria decision problems. EXPERT SYSTEMS WITH APPLICATIONS, v. 122, p. 262-280, . (17/23879-9, 16/21571-4)
PELEGRINA, GUILHERME DEAN; DUARTE, LEONARDO TOMAZELI; GRABISCH, MICHEL; ROMANO, JOAO MARCOS TRAVASSOS. Dealing with redundancies among criteria in multicriteria decision making through independent component analysis. COMPUTERS & INDUSTRIAL ENGINEERING, v. 169, p. 19-pg., . (20/01089-9, 17/23879-9, 20/09838-0, 16/21571-4)
PELEGRINA, GUILHERME DEAN; DUARTE, LEONARDO TOMAZELI; TRAVASSOS ROMANO, JOAO MARCOS; DEVILLE, Y; GANNOT, S; MASON, R; PLUMBLEY, MD; WARD, D. Muticriteria Decision Making Based on Independent Component Analysis: A Preliminary Investigation Considering the TOPSIS Approach. LATENT VARIABLE ANALYSIS AND SIGNAL SEPARATION (LVA/ICA 2018), v. 10891, p. 10-pg., . (16/21571-4, 17/23879-9)
PELEGRINA, GUILHERME DEAN; DUARTE, LEONARDO TOMAZELI; GRABISCH, MICHEL; TRAVASSOS ROMANO, JOAO MARCOS; TORRA, V; NARUKAWA, Y; NIN, J; AGELL, N. An Unsupervised Capacity Identification Approach Based on Sobol' Indices. MODELING DECISIONS FOR ARTIFICIAL INTELLIGENCE (MDAI 2020), v. 12256, p. 12-pg., . (17/23879-9, 16/21571-4)
PELEGRINA, GUILHERME DEAN; DUARTE, LEONARDO TOMAZELI; GRABISCH, MICHEL; TRAVASSOS ROMANO, JOAO MARCOS. The multilinear model in multicriteria decision making: The case of 2-additive capacities and contributions to parameter identification. European Journal of Operational Research, v. 282, n. 3, p. 945-956, . (16/21571-4, 17/23879-9)

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