Skip to main content
Log in

An interactive fuzzy satisficing method based on variance minimization under expectation constraints for multiobjective stochastic linear programming problems

  • Original Paper
  • Published:
Soft Computing Aims and scope Submit manuscript

Abstract

In this paper, we focus on multiobjective linear programming problems involving random variable coefficients in objective functions and constraints. Using the concept of chance constrained conditions, such multiobjective stochastic linear programming problems are transformed into deterministic ones based on the variance minimization model under expectation constraints. After introducing fuzzy goals to reflect the ambiguity of the decision maker’s judgements for objective functions, we propose an interactive fuzzy satisficing method to derive a satisficing solution for them as a fusion of the stochastic programming and the fuzzy one. The application of the proposed method to an illustrative numerical example shows its usefulness.

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.

Fig. 1
Fig. 2

Similar content being viewed by others

References

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kosuke Kato.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kato, K., Sakawa, M. An interactive fuzzy satisficing method based on variance minimization under expectation constraints for multiobjective stochastic linear programming problems. Soft Comput 15, 131–138 (2011). https://doi.org/10.1007/s00500-010-0540-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-010-0540-z

Keywords

Navigation