Title
ELECTREGKMS: Robust ordinal regression for outranking methods.
Abstract
We present a new method, called ELECTREGKMS, which employs robust ordinal regression to construct a set of outranking models compatible with preference information. The preference information supplied by the decision maker (DM) is composed of pairwise comparisons stating the truth or falsity of the outranking relation for some real or fictitious reference alternatives. Moreover, the DM specifies some ranges of variation of comparison thresholds on considered pseudo-criteria. Using robust ordinal regression, the method builds a set of values of concordance indices, concordance thresholds, indifference, preference, and veto thresholds, for which all specified pairwise comparisons can be restored. Such sets are called compatible outranking models. Using these models, two outranking relations are defined, necessary and possible. Whether for an ordered pair of alternatives there is necessary or possible outranking depends on the truth of outranking relation for all or at least one compatible model, respectively. Distinguishing the most certain recommendation worked out by the necessary outranking, and a possible recommendation worked out by the possible outranking, ELECTREGKMS answers questions of robustness concern. The method is intended to be used interactively with incremental specification of pairwise comparisons, possibly with decreasing confidence levels. In this way, the necessary and possible outranking relations can be, respectively, enriched or impoverished with the growth of the number of pairwise comparisons. Furthermore, the method is able to identify troublesome pieces of preference information which are responsible for incompatibility. The necessary and possible outranking relations are to be exploited as usual outranking relations to work out recommendation in choice or ranking problems. The introduced approach is illustrated by a didactic example showing how ELECTREGKMS can support real-world decision problems. (C) 2011 Elsevier B.V. All rights reserved.
Year
DOI
Venue
2011
10.1016/j.ejor.2011.03.045
European Journal of Operational Research
Keywords
DocType
Volume
Robust ordinal regression,Outranking relation,Multiple criteria ranking and choice,ELECTRE-like method
Journal
214
Issue
ISSN
Citations 
1
0377-2217
37
PageRank 
References 
Authors
1.80
8
4
Name
Order
Citations
PageRank
Salvatore Greco13977266.79
Milosz Kadzinski221018.36
Vincent Mousseau380850.52
Roman Slowinski45561516.06