Publication:
Application and comparison of CC-integrals in business group decision making

Consultable a partir de

Date

2022

Authors

Wieczynski, Jonata
Borges, Eduardo N.
Lourenzutti, Rodolfo

Director

Publisher

Springer
Acceso abierto / Sarbide irekia
Contribución a congreso / Biltzarrerako ekarpena
Versión aceptada / Onetsi den bertsioa

Project identifier

//PC093-094TFIPDL
//TIN2016-81731-REDT
//TIN2016-77356-P

Abstract

Optimized decisions is required by businesses (analysts) if they want to stay open. Even thought some of these are from the knowhow of the managers/executives, most of them can be described mathematically and solved (semi)-optimally by computers. The Group Modular Choquet Random Technique for Order of Preference by Similarity to Ideal Solution (GMC-RTOPSIS) is a Multi-Criteria Decision Making (MCDM) that was developed as a method to optimize the later types of problems, by being able to work with multiple heterogeneous data types and interaction among different criteria. On the other hand the Choquet integral is widely used in various fields, such as brain-computer interfaces and classification problems. With the introduction of the CC-integrals, this study presents the GMC-RTOPSIS method with CC-integrals. We applied 30 different CC-integrals in the method and analyzed its results using 3 different methods. We found that by modifying the decisionmaking method we allow for more flexibility and certainty in the choosing process.

Description

Keywords

CC-integral, Decision making, Generalized choquet integral, GMC-RTOPSIS

Department

Estadística, Informática y Matemáticas / Estatistika, Informatika eta Matematika

Faculty/School

Degree

Doctorate program

item.page.cita

Wieczynski, J., Lucca, G., Borges, E., Dimuro, G., Lourenzutti, R., & Bustince, H. (2022). Application and comparison of cc-integrals in business group decision making. En J. Filipe, M. Śmiałek, A. Brodsky, & S. Hammoudi (Eds.), Enterprise Information Systems (Vol. 455, pp. 129-148). Springer International Publishing. https://doi.org/10.1007/978-3-031-08965-7_7

item.page.rights

© 2022 Springer Nature Switzerland AG.

Los documentos de Academica-e están protegidos por derechos de autor con todos los derechos reservados, a no ser que se indique lo contrario.