Skip to main content

The Aggregation of Industrial Performance Information by the Choquet Fuzzy Integral

  • Chapter
Soft Computing in Measurement and Information Acquisition

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 127))

Abstract

This study deals with the aggregation of industrial performance information, i.e. with the mechanism which allows the computation of a global performance knowing the partial ones. The performance information is aimed at controlling the production activity, by indicating how the real objective is reached. The characteristics of this kind of aggregation is that the partial performances to be aggregated are, on the one hand, often information of heterogeneous nature (dimension, format). On the other hand, they are associated to diversified and numerous objectives which interacts in different ways (redundant, complementary,...). In this sense, the fuzzy subset theory provides tools to deal with: the heterogeneity of the entities involved, the commensurability of the partial performances expressed in the interval [0,1], and the different behaviors of the aggregation operation (compromise effect, optimistic or pessimistic effect,...). Among all the fuzzy aggregation operators, we consider here, as an illustration, one use of the Choquet fuzzy integral family for modeling the different interactions between the objectives and aggregating their associated performances.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bellman, R. and L.A. Zadeh, Decision-making in a fuzzy environment, Management Sciences 17, 1970, pp. B141 - B164.

    Article  MATH  Google Scholar 

  2. Berrah, L., G. Mauris, L. Foulloy and A. Haurat, Global vision and performance indicators for an industrial improvement approach, Computers in Industry, to be published in 2000.

    Google Scholar 

  3. Bititci, S., Modelling of performance measurement systems in manufacturing entreprises, Int. Journal of Production Economics, Vol. 42, 1995, pp. 137–147.

    Article  Google Scholar 

  4. D. Dubois and H. Prade, A unifying view of comparison indices, in Fuzzy sets and possibility theory recent advances, eds. Pergamon Press, 1982, pp. 3–13.

    Google Scholar 

  5. Dubois, D., H. Prade and C. Testemale, Weighted fuzzy pattern matching, Fuzzy Sets and Systems 28, 1988, pp. 313–331.

    Article  MathSciNet  MATH  Google Scholar 

  6. Fortuin, L., Performance indicators–why, where and how,European Journal of Operational Research, Vol. 34, 1988, pp. 1–9.

    Google Scholar 

  7. Globerson, S., Issues in developing a performance criteria system for an organization, Int. Journal of Production Research, Vol. 23, No 4, 1985, pp. 639–646.

    Article  Google Scholar 

  8. Grabisch, M., On equivalence classes of fuzzy connectives — The case of fuzzy integrals, IEEE Trans. On Fuzzy Systems, Vol. 3, No 1, 1995, pp. 96–109.

    Article  Google Scholar 

  9. Grabisch, M., Alternative representations of discrete fuzzy measures for decision making, Int. Journal of Uncertainty, Fuzziness and Knowledge-based Systems, No 5, 1997, pp. 587–607.

    Article  MathSciNet  MATH  Google Scholar 

  10. Grabisch, M., Murofushi, T. and M. Sugeno, Fuzzy measures and integrals: theory and applications, Physica-Verlag, 2000.

    Google Scholar 

  11. Kaplan, R.S. and D.P. Norton, Using the balanced scorecard as a strategic management, Harvard Business Review, Jan/Feb 1996, pp. 77–85.

    Google Scholar 

  12. Marichal, J.L., Agrégation de critères interactifs au moyen de l’intégrale de Choquet discrète, Rencontres francoph. sur la logique floue et ses applications LFA’99, Valenciennes, France, 1999, pp. 130–140.

    Google Scholar 

  13. Rangone, A., An analytical hierarchy process framework for comparing the overall performance of manufacturing departments, Int. Journal of Operations and Production Management, Vol. 16, No 8, 1996, pp. 104–119.

    Article  Google Scholar 

  14. Saaty, T., A scaling method for priorities in hierarchical strutures, Journal of Mathematical Psychology, Vol. 15, 1977, pp. 234–281.

    Article  MathSciNet  MATH  Google Scholar 

  15. Zadeh, L.A., Fuzzy sets, Information and Control, Vol. 8, 1965, pp. 338–353.

    Article  MathSciNet  MATH  Google Scholar 

  16. Zadeh L.A., Quantitative fuzzy semantics,Information Sciences, 3, 1971, pp. 159–171.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2003 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Berrah, L., Mauris, G., Foulloy, L. (2003). The Aggregation of Industrial Performance Information by the Choquet Fuzzy Integral. In: Reznik, L., Kreinovich, V. (eds) Soft Computing in Measurement and Information Acquisition. Studies in Fuzziness and Soft Computing, vol 127. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-36216-6_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-36216-6_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-53509-3

  • Online ISBN: 978-3-540-36216-6

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics