Ranking of qualitative decision options using copulas

Conference paper
Part of the Operations Research Proceedings book series (ORP)

Abstract

We study the ranking of classified multi-attribute qualitative options. To obtain a full ranking of options within classes, qualitative options are mapped into quantitative ones. Current approaches, such as the Qualitative-Quantitative (QQ) method, use linear functions for ranking, hence performing well for linear and monotone options; however QQ underperforms in cases of non-linear and nonmonotone options. To address this problem, we propose a new QQ-based method in which we introduce copulas as an aggregation utility instead of linear functions. In addition, we analyze the behavior of different hierarchical structures of bivariate copulas to model the non-linear dependences among attributes and classes.

Keywords

Archimedean Copula Linear Regression Function Clayton Copula Copula Family Inverse Cumulative Distribution Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Jožef Stefan InstituteLjubljanaSlovenia
  2. 2.University of Nova GoricaNova GoricaSlovenia

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