References of "Bisdorff, Raymond 50000801"
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See detailElicitation of criteria weights maximising the stability of pairwise outranking statements
Bisdorff, Raymond UL; Meyer, P.; Veneziano, T.

in Journal of Multi-Criteria Decision Analysis (2014), 21(1-2), 113-124

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See detailDocumentation of the Digraph3 Python software resources
Bisdorff, Raymond UL

Software (2014)

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See detailThe Electre like outranking approach to MCDA
Bisdorff, Raymond UL

Presentation (2013, August)

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See detailDescriptive profiles for sets of alternatives in multiple criteria decision aid
Olteanu, A.-L.; Meyer, P.; Bisdorff, Raymond UL

in Lecture Notes in Computer Science (2013), 8176 LNAI

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See detailOn polarizing outranking relations with large performance differences
Bisdorff, Raymond UL

in Journal of Multi-Criteria Decision Analysis (2013), 20

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See detailAlgorithmic Decision Theory
Bisdorff, Raymond UL

Scientific Conference (2012, December)

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See detailOn measuring and testing the ordinal correlation between bipolar outranking relations
Bisdorff, Raymond UL

Scientific Conference (2012, November 15)

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See detailOn polarizing outranking relations with large performance differences
Bisdorff, Raymond UL

Scientific Conference (2012, February)

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See detailAide à la Décision Concentrée sur l'Expertise Humaine
Bisdorff, Raymond UL

Scientific Conference (2011, June 21)

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See detailK-Sorting with multiple ordinal criteria
Bisdorff, Raymond UL

Scientific Conference (2011, February 10)

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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 detailModern MCDA software: requirements and opportunities
Bisdorff, Raymond UL

Report (2011)

Complexity, credibility and change are three inevitable issues we face in modern decision-making problems. Integrating modern software requirements like rich user interaction, distributed architecture ... [more ▼]

Complexity, credibility and change are three inevitable issues we face in modern decision-making problems. Integrating modern software requirements like rich user interaction, distributed architecture, agile application life-cycle development and full traceability may give the adequate answer to master these issues with our MCDA software. [less ▲]

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See detailOn a bipolar foundation of the outranking concept
Bisdorff, Raymond UL

Scientific Conference (2010, April 14)

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See detailOn detecting and enumerating chordless circuits in a digraph
Bisdorff, Raymond UL

E-print/Working paper (2010)

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See detailEnumerating chordless circuits in directed graphs
Bisdorff, Raymond UL

Scientific Conference (2010, January 28)

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See detailThe Decision Deck Project
Bisdorff, Raymond UL

Report (2009)

The Decision Deck project is developing an open-source generic Multiple Criteria Decision Aid (MCDA) software platform composed of modular components. Its purpose is to provide effective tools for ... [more ▼]

The Decision Deck project is developing an open-source generic Multiple Criteria Decision Aid (MCDA) software platform composed of modular components. Its purpose is to provide effective tools for decision-aid consultants, for researchers in the field of MCDA, and for operations research teachers. [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 detailOn Clustering the Criteria in an Outranking Based Decision Aid Approach
Bisdorff, Raymond UL

in Communications in Computer and Information Science (2008), 14

Detailed reference viewed: 79 (1 UL)