Institutional Repository
Technical University of Crete
EN  |  EL

Search

Browse

My Space

Multiple criteria hierarchy process for sorting problems based on ordinal regression with additive value functions

Michael Doumpos, Zopounidis Konstantinos, Corrente Salvatore, Greco Salvatore, Słowiński, Roman

Full record


URI: http://purl.tuc.gr/dl/dias/59CA9DE6-6C34-4C2E-BAEA-7B3273463F6D
Year 2017
Type of Item Peer-Reviewed Journal Publication
License
Details
Bibliographic Citation S. Corrente, M. Doumpos, S. Greco, R. Słowiński and C. Zopounidis "Multiple criteria hierarchy process for sorting problems based on ordinal regression with additive value functions," Annals Operat. Res., vol. 151, no. 1-2, pp. 117–139, Apr. 2017. doi:10.1007/s10479-015-1898-1 https://doi.org/10.1007/s10479-015-1898-1
Appears in Collections

Summary

A hierarchical decomposition is a common approach for coping with complex decision problems involving multiple dimensions. Recently, the multiple criteria hierarchy process (MCHP) has been introduced as a new general framework for dealing with multiple criteria decision aiding in case of a hierarchical structure of the family of evaluation criteria. This study applies the MCHP framework to multiple criteria sorting problems and extends existing disaggregation and robust ordinal regression techniques that induce decision models from data. The new methodology allows the handling of preference information and the formulation of recommendations at the comprehensive level, as well as at all intermediate levels of the hierarchy of criteria. A case study on bank performance rating is used to illustrate the proposed methodology.

Services

Statistics