References of "Meyer, Patrick"
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See detailA Clustering Approach using Weighted Similarity Majority Margins
Bisdorff, Raymond UL; Meyer, Patrick; Olteanu, Alexandru UL

in Advanced Data Mining and Applications ADMA, Beijing spring 2013 (2011)

We propose a meta-heuristic for clustering objects that are described on multiple incommensurable attributes of nominal, ordinal and/or cardinal type. Our approach makes use of an innovative bipolar ... [more ▼]

We propose a meta-heuristic for clustering objects that are described on multiple incommensurable attributes of nominal, ordinal and/or cardinal type. Our approach makes use of an innovative bipolar-valued dual similarity-dissimilarity relation characterized by pairwise weighted majority margins of similar minus dissimilar attribute evaluations. The clustering is computed in two steps. First, an evolutionary algorithm searches for a suitable subset of maximal similarity cliques that will best serve as cluster cores. In a second step, we construct with a greedy heuristic, around these initial cluster cores, a corresponding final partition which best fits the given bipolar-valued similarity relation. [less ▲]

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See detailInverse analysis from a Condorcet robustness denotation of valued outranking relations
Bisdorff, Raymond UL; Meyer, Patrick; Veneziano, Thomas UL

in Rossi, Francesca; Tsoukiás, Alexis (Eds.) Algorithmic Decision Theory (2009)

In this chapter we develop an indirect approach for assessing criteria significance weights from the robustness of the significance that a decision maker acknowledges for his pairwise outranking ... [more ▼]

In this chapter we develop an indirect approach for assessing criteria significance weights from the robustness of the significance that a decision maker acknowledges for his pairwise outranking statements in a Multiple Criteria Decision Aiding process. The main result consists in showing that with the help of a mixed integer linear programming model this kind of a priori knowledge is sufficient for estimating adequate numerical significance weights. [less ▲]

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See detailDisaggregation of bipolar-valued outranking relations
Meyer, Patrick; Marichal, Jean-Luc UL; Bisdorff, Raymond UL

in Le Thi, Hoai An; Bouvry, Pascal; Pham Dinh, Tao (Eds.) Modelling, Computation and Optimization in Information Systems and Management Sciences (2008, August 28)

In this article, we tackle the problem of exploring the structure of the data which is underlying a bipolar-valued outranking relation. More precisely, we show how the performances of alternatives and ... [more ▼]

In this article, we tackle the problem of exploring the structure of the data which is underlying a bipolar-valued outranking relation. More precisely, we show how the performances of alternatives and weights related to criteria can be determined from three different formulations of the bipolar-valued outranking relations, which are given beforehand. [less ▲]

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See detailDisaggregation of bipolar-valued outranking relations and application to the inference of model parameters
Meyer, Patrick; Marichal, Jean-Luc UL; Bisdorff, Raymond UL

Scientific Conference (2007, September)

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See detailSorting multiattribute alternatives: The TOMASO method
Marichal, Jean-Luc UL; Meyer, Patrick; Roubens, Marc

in Computers & Operations Research (2005), 32(4), 861-877

We analyze a recently proposed ordinal sorting procedure (Tomaso) for the assignment of alternatives to graded classes and we present a freeware constructed from this procedure. We illustrate it by two ... [more ▼]

We analyze a recently proposed ordinal sorting procedure (Tomaso) for the assignment of alternatives to graded classes and we present a freeware constructed from this procedure. We illustrate it by two examples, and do some testing in order to show its usefulness. [less ▲]

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See detailTOMASO, A solution in the presence of interacting points of views
Meyer, Patrick; Roubens, Marc; Marichal, Jean-Luc UL

Article for general public (2004)

This short article briefly presents the main features of the multiple criteria sorting tool TOMASO (Technique for Ordinal Multi-Attribute Sorting and Ordering) and its implementation. Its main ... [more ▼]

This short article briefly presents the main features of the multiple criteria sorting tool TOMASO (Technique for Ordinal Multi-Attribute Sorting and Ordering) and its implementation. Its main particularities are the possibility to consider interacting points of view and the use of the Choquet integral as a discriminant function. The capacities are learnt through the use of protoypes, which are well known alternatives for the Decision Maker. [less ▲]

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