International Journal of Applied Science and Engineering
Published by Chaoyang University of Technology

Amit Kumar and Neha Bhatia1 

School of Mathematics and Computer Applications Thapar University, Patiala-147004, India


Download Citation: |
Download PDF


ABSTRACT


Kheirfam and Hasani (Sensitivity analysis for fuzzy linear programming problems with fuzzy variables, Advanced Modeling and Optimization, 12 (2010) 257-272), proposed a new method to deal with the sensitivity analysis of such fuzzy linear programming (FLP) problems in which all the elements of coefficient matrix of the constraints and the coefficients of the decision variables in the objective function are represented by real numbers and remaining parameters are represented by trapezoidal fuzzy numbers. In this paper, it is shown that the existing method can’t be used for solving sensitivity analysis of such FLP problems in which only the elements coefficient matrix of constraints are represented by real numbers and other parameters are represented by trapezoidal fuzzy numbers. To overcome this limitation of existing method, a new method, named as Mehar’s method, is proposed to deal with the sensitivity analysis of FLP problems. The main advantage of Mehar’s method over existing method is that Mehar’s method is easy to apply as compare to existing method and can be used to deal with the sensitivity analysis of both type of fuzzy sensitivity analysis problem. To show the advantages of the Mehar’s method over existing method some fuzzy sensitivity analysis problems, which may or may not be solved by using existing methods, are solved by using Mehar’s method.


Keywords: fuzzy linear programming problems; ranking function; sensitivity analysis; trapezoidal fuzzy numbers.


Share this article with your colleagues

 


REFERENCES


  1. [1] Dutta, D. Rao, J. R., and Tiwari R., N. 1992. Sensitivity analysis in fuzzy linear fractional programming problem, Fuzzy Sets and Systems, 48: 211-216.

  2. [2] Fuller, R. 1989. On stability in fuzzy linear programming problems, Fuzzy Sets and Systems, 30: 339-344.

  3. [3] Gupta, P. and Bhatia, D. 2001. Sensitivity analysis in fuzzy multi-objective linear fractional programming problem, Fuzzy Sets and Systems, 122: 229-236.

  4. [4] Hamacher, H. Leberling, H., and Zimmermann, H. J. 1978. Sensitivity analysis in fuzzy linear programming, Fuzzy Sets and Systems, 1: 269-281.

  5. [5] Kaufmann, A. and Gupta, M. M. Introduction to fuzzy arithmetics: Theory and applications, Newyork: Van Nostrand Reinhold, 1991.

  6. [6] Kheirfam, B. and Hasani, F. 2010. Sensitivity analysis for fuzzy linear programming problems with fuzzy variables, Advanced Modeling and Optimization, 12: 257- 272.

  7. [7] Lotfi, F. H., Jondabeh, M. A., and Faizrahnemoon, M. 2010. Senstivity analysis in fuzzy environment, Applied Mathematical Sciences, 4: 1635-1646.

  8. [8] Precup, R. E. and Preitl, S. 2006. Stability and sensitivity analysis of fuzzy control systems, Mechatronics Applications, 3: 61-76.

  9. [9] Sakawa, M. and Yano, H. 1988. An interactive fuzzy satisfying method for multi-objective linear fractional programming problems, Fuzzy Sets and Systems, 28: 129-144.

  10. [10] Tanaka, H. and Asai, K. 1984. Fuzzy linear programming with fuzzy number, Fuzzy Sets and Systems, 13: 1-10.

  11. [11] Tanaka, H., Ichihashi, H., and Asai, K. 1986. A value of information in fuzzy linear programming problems via sensitivity analysis, Fuzzy Sets and Systems, 18: 119-129.

  12. [12] Verdegay, J. L. and Aguado, G. 1993. On the sensitivity of membership func-tion for fuzzy linear programming problem, Fuzzy Sets and Systems, 56: 47-49.

  13. [13] Yager, R. R. 1981. A procedure for ordering fuzzy subsets of the unit interval, Information Sciences, 24: 143-161.

  14. [14] Zadeh, L. A. 1965. Fuzzy sets, Information and Control, 8: 338-353.

  15. [15] Zimmerman, H. J. 1976. Description and optimization of fuzzy systems, International Journal of General Systems, 2: 209-215.


ARTICLE INFORMATION




Accepted: 2011-03-03
Publication Date: 2011-06-01


Cite this article:

Kumar, A., Bhatia, N. 2011. A new method for solving fuzzy sensitivity analysis problems. International Journal of Applied Science and Engineering, 9, 49–64. https://doi.org/10.6703/IJASE.2011.9(2).49


We use cookies on this website to improve your user experience. By using this site you agree to its use of cookies.