Preference and causal fuzzy models for manager's decision aiding in industrial performance improvement

Abstract : The design and use of Performance Measurement Systems (PMS's) for industrial improvement and control have received considerable attention in recent years. Indeed, industrial performances are now defined in terms of numerous and multi-level criteria to be synthesized for overall improvement purposes. This article is a contribution to the decision-maker's information needs for optimizing the improvement of an overall performance versus the allocated resources and for choosing the right actions in order to achieve the required overall performance. The latter is decomposed into elementary performances according to decision-makers' preferences represented by a fuzzy integral aggregation. The causes-effects links between possible actions and performances are represented by a fuzzy ordinal influence model. The proposed fuzzy models are both applied for improvement actions selection on a case study submitted by a company manufacturing kitchens and bathrooms.
Type de document :
Communication dans un congrès
2010 IEEE WORLD CONGRESS ON COMPUTATIONAL INTELLIGENCE 2010 IEEE Conference on Fuzzy Systems JULY 18-23, 2010, BARCELONA, SPAIN, Jul 2010, Barcelona, Spain. pp.Proceedings on CD ROM, 2010
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http://hal.univ-smb.fr/hal-00527726
Contributeur : Vincent Clivillé <>
Soumis le : mercredi 20 octobre 2010 - 10:32:58
Dernière modification le : vendredi 9 février 2018 - 16:58:06

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  • HAL Id : hal-00527726, version 1

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Jacky Montmain, Vincent Clivillé, Lamia Berrah, Gilles Mauris. Preference and causal fuzzy models for manager's decision aiding in industrial performance improvement. 2010 IEEE WORLD CONGRESS ON COMPUTATIONAL INTELLIGENCE 2010 IEEE Conference on Fuzzy Systems JULY 18-23, 2010, BARCELONA, SPAIN, Jul 2010, Barcelona, Spain. pp.Proceedings on CD ROM, 2010. 〈hal-00527726〉

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