Skip to main content
Log in

Fuzzy Linear Programming with Interactive Uncertain Parameters

  • Published:
Reliable Computing

Abstract

In this paper, we treat fuzzy linear programming problems with uncertain parameters whose ranges are specified as fuzzy polytopes. The problem is formulated based on fractile optimization model using a necessity measure. It is shown that the problem can be reduced to a semi-infinite linear programming problem and that a solution algorithm based on a relaxation procedure can be applied. A simple numerical example is given to illustrate the solution procedure.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Blankenship, J. W. and Falk, J. E.: Infinitely Constrained Optimization Problems, Journal of Optimization Theory and Applications 19 (1976), pp. 261–281.

    Article  MATH  MathSciNet  Google Scholar 

  2. Dubois, D. and Prade, H.: Fuzzy Sets and Systems: Theory and Applications, Academic Press, 1980.

  3. Dubois, D. and Prade, H.: Possibility Theory: An Approach to Computerized Processing Uncertainty, Plenum, 1988.

  4. Inuiguchi, M. and Ichihashi, H.: Relative Modalities and Their Use in Possibilistic Linear Programming, Fuzzy Sets and Systems 35(3) (1990), pp. 303–323.

    Article  MATH  MathSciNet  Google Scholar 

  5. Inuiguchi, M., Ichihashi, H., and Kume, Y.: Modality Constrained Programming Problems: A Unified Approach to Fuzzy Mathematical Programming Problems in the Setting of Possibility Theory, Information Sciences 67 (1993), pp. 93–126.

    Article  MATH  MathSciNet  Google Scholar 

  6. Inuiguchi, M., Ramík, J., and Tanino, T.: Oblique Fuzzy Vectors and Their Use in Possibilistic Linear Programming, Fuzzy Sets and Systems 137(1) (2003), pp. 123–150.

    Article  Google Scholar 

  7. Inuiguchi, M. and Sakawa, M.: A Possibilistic Linear Program Is Equivalent to a Stochastic Linear Program in a Special Case, Fuzzy Sets and Systems 76 (1995), pp. 309–318.

    Article  MATH  MathSciNet  Google Scholar 

  8. Inuiguchi, M. and Tanino, T.: Possibilistic Linear Programming with Fuzzy If-Then Rule Coefficients, Fuzzy Optimization and Decision Making 1(1) (2002), pp. 65–91.

    Article  MATH  MathSciNet  Google Scholar 

  9. Rommelfanger, H.: Fuzzy Linear Programming and Applications, European Journal of Operational Research 92(3) (1996), pp. 512–527.

    Article  MATH  MathSciNet  Google Scholar 

  10. Rommelfanger, H. and Keresztfalvi, T.: Multicriteria Fuzzy Optimization Based on Yager's Parameterized t-Norm, Foundation of Computing and Decision Sciences 16(2) (1991).

  11. Słowiński, R. and Teghem, J. (eds): Stochastic versus Fuzzy Approaches to Multiobjective Mathematical Programming under Uncertainty, Kluwer Academic Publishers, Dordrecht, 1990.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Masahiro Inuiguchi.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Inuiguchi, M., Tanino, T. Fuzzy Linear Programming with Interactive Uncertain Parameters. Reliable Computing 10, 357–367 (2004). https://doi.org/10.1023/B:REOM.0000032118.34323.f2

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/B:REOM.0000032118.34323.f2

Keywords

Navigation