A stochastic method for robustness analysis in sorting problems

Tervonen, Tommi; Figueira, José Rui; Lahdelma, Risto; Dias, Juscelino Almeida; Salminen, Pekka

doi:10.1016/j.ejor.2007.09.008

Cited by 149 publications

(56 citation statements)

References 22 publications

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“…Extensions of FlowSort [50,51] and other methods for multicriteria sorting, such as ELECTRE-Tri [52] and its modifications for uncertainty treatment [53] , have also been used for analysis of problems on strategic planning and risk management.…”

Section: Flowsort (Sorting Methods With the Use Of Net Flows)mentioning

confidence: 99%

Decerns: A Framework for Multi-Criteria Decision Analysis

Yatsalo¹,

Didenko²,

Gritsyuk³

et al. 2015

IJCIS

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A new framework, Decerns, for multicriteria decision analysis (MCDA) of a wide range of practical problems on risk management is introduced. Decerns framework contains a library of modules that are the basis for two scalable systems: DecernsMCDA for analysis of multicriteria problems, and DecernsSDSS for multicriteria analysis of spatial options. DecernsMCDA includes well known MCDA methods and original methods for uncertainty treatment based on probabilistic approaches and fuzzy numbers. These MCDA methods are described along with a case study on analysis of multicriteria location problem.

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Section: Flowsort (Sorting Methods With the Use Of Net Flows)mentioning

confidence: 99%

Decerns: A Framework for Multi-Criteria Decision Analysis

Yatsalo¹,

Didenko²,

Gritsyuk³

et al. 2015

IJCIS

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“…Dividing alternatives into groups are among favourite research fields in various disciplines. The SMAA-TRI is one of the useful methods for sorting, because it does not need weight elicitation [58]. The method is an improved form of ELECTRE-TRI to use stochastic values.…”

Section: Stochastic Multi-criteria Acceptability Analysis (Smaa)mentioning

confidence: 99%

Mathematical Model and Stochastic Multi-Criteria Acceptability Analysis for Facility Location Problem

Karabay

Köse

Kabak

et al. 2016

PROMET

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“…The latter is important if uncertainties arise in the performances of some alternatives. Other approaches in this spirit aim at justifying the suggested recommendation in terms of minimal pieces of preference information that make them true (called preferential reducts) [20] or stochastic analysis indicating an estimate of the probability of a possible preference relation, attaining some rank [25] or assignment [37]. We perceive the proposed post factum analysis as a complementary methodology to MCDA which, until now, concentrated mainly on providing a recommendation based on a preference model compatible with preference information provided by the DM.…”

Section: Indirect and Imprecise Preference Informationmentioning

confidence: 99%

Post factum analysis for robust multiple criteria ranking and sorting

et al. 2015

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Providing partial preference information for multiple criteria ranking or sorting problems results in the indetermination of the preference model. Investigating the influence of this indetermination on the suggested recommendation, we may obtain the necessary, possible and extreme results confirmed by, respectively, all, at least one, or the most and least advantageous preference model instances compatible with the input preference information. We propose a framework for answering questions regarding stability of these results. In particular, we are investigating the minimal improvement that warrants feasibility of some currently impossible outcome as well as the maximal deterioration by which some already attainable result still holds. Taking into account the setting of multiple criteria ranking and sorting problems, we consider such questions in view of pairwise preference relations, or attaining some rank, or assignment. The improvement or deterioration of the sort of an alternative is quantified with the change of its performances on particular criteria and/or its comprehensive score. The proposed framework is useful in terms of design, planning, formulating the guidelines, or defining the future performance targets. It is also important for robustness concern because it finds which parts of the recommendation are robust or sensitive with respect to the modification of the alternatives' performance values or scores. Application of the proposed approach is demonstrated on the problem of assessing environmental impact of main European cities.

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A stochastic method for robustness analysis in sorting problems

Cited by 149 publications

References 22 publications

Decerns: A Framework for Multi-Criteria Decision Analysis

Decerns: A Framework for Multi-Criteria Decision Analysis

Mathematical Model and Stochastic Multi-Criteria Acceptability Analysis for Facility Location Problem

Post factum analysis for robust multiple criteria ranking and sorting

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