A decade of application of the Choquet and Sugeno integrals in multi-criteria decision aid

Grabisch, Michel; Labreuche, Christophe

doi:10.1007/s10288-007-0064-2

Cited by 273 publications

(264 citation statements)

References 77 publications

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“…This function is a very general aggregation function which can model a wide range of decisional behaviours. In particular, it is parameterised by a set function, called fuzzy measure or capacity, for which efficient elicitation processes have been created (Grabisch and Roubens, 2000;Labreuche and Grabisch, 2003). Finally, for the integration of an MCDM model in CP, we recall four conditions, previously introduced in Le Huédé et al (2002).…”

Section: Modelling Multicriteria Preferencesmentioning

confidence: 99%

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MCS—A new algorithm for multicriteria optimisation in constraint programming

et al. 2006

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In this paper we propose a new algorithm called MCS for the search for solutions to multicriteria combinatorial optimisation problems. To quickly produce a solution that offers a good trade-off between criteria, the MCS algorithm alternates several Branch & Bound searches following diversified search strategies. It is implemented in CP in a dedicated framework and can be specialised for either complete or partial search.

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Section: Modelling Multicriteria Preferencesmentioning

confidence: 99%

“…In the MCDM methodology, the fuzzy measure is established in order to model the decision maker preferences (Grabisch and Roubens, 2000). Then, the mono-dimensional utilities u 1 , .…”

Section: The Choquet Integralmentioning

confidence: 99%

MCS—A new algorithm for multicriteria optimisation in constraint programming

et al. 2006

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“…It allows to solve MCDA problems via Choquet integral-based MAVT and contains all the identification methods proposed in the literature as well as our personal contributions (see also Grabisch and Labreuche 2008).…”

Section: On Choquet Integral-based Mavt and Kappalabmentioning

confidence: 99%

Progressive methods in multiple criteria decision analysis

Meyer

2008

4OR-Q J Oper Res

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This is a summary of the author's Ph.D. thesis, defended on 8 October 2007 at the University of Luxembourg and the Faculté Polytechnique de Mons, under the joint supervision of Raymond Bisdorff and Marc Pirlot. The thesis is written in English and is available from the author upon request. The work is situated in the field of multiple criteria decision analysis. It mostly deals with what we call progressive methods, i.e., iterative procedures presenting partial conclusions to the decision maker that can be refined at further steps of the analysis. Such progressive methods have been studied in the context of multiattribute value theory and outranking methods.Keywords Multiple criteria decision analysis · Progressive methods · Choquet integral · Multiattribute value theory · Bipolar-valued outranking relation MSC classification (2000) 05C20 · 90B50

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“…The first one, called partial aggregation approaches, consists in comparing the different possible decisions per pair by the means of outranking relations [9], [10]. The second family of approaches, called complete aggregation approaches, consists in aggregating all criteria in a single criterion (utility function) which is then used to make the decision [11], [12], [13]. The last family of approaches, which is highly interactive, consists in devising a preliminary decision and in comparing it with other possible decisions to determine the best one [14], [15].…”

Section: A State Of the Art Of Multi-criteria Decision Making Methodsmentioning

confidence: 99%

Using the PROMETHEE multi-criteria decision making method to define new exploration strategies for rescue robots

Taillandier

Stinckwich

2011

2011 IEEE International Symposium on Safety, Security, and Rescue Robotics

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To cite this version:Patrick Taillandier, Serge Stinckwich. Using the PROMETHEE multi-criteria decision making method to define new exploration strategies for rescue robots. IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), 2011, Kyoto, Japan. pp. 321 -326, 2011321 -326, , <10.1109321 -326, /SSRR.2011 Using the PROMETHEE Abstract -The exploration of an unknown environment by a robot system (an individual robot or a team of robots) is a well-studied problem in robotics. This problem has many applications and, among them, the post-disaster search of victims in an urban space. Most of proposed exploration algorithms are based on the use of specific criteria to define the quality of the possible movements. In this paper, we propose an exploration approach based on the combination of several criteria thanks to the PROMETHEE II multi-criteria decision making method. The PROMETHEE II method allows one to establish a complete ranking between possible movements based on outranking relations. Experimental results show that this approach can be used to effectively combine different criteria and outperforms several classic exploration strategies.

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A decade of application of the Choquet and Sugeno integrals in multi-criteria decision aid

Cited by 273 publications

References 77 publications

MCS—A new algorithm for multicriteria optimisation in constraint programming

MCS—A new algorithm for multicriteria optimisation in constraint programming

Progressive methods in multiple criteria decision analysis

Using the PROMETHEE multi-criteria decision making method to define new exploration strategies for rescue robots

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