A Case study on an Economic problem by using Fuzzy linear Equations

Authors

  • Rupjit Saikia  Department of Mathematics, Dibrugarh University, Dibrugarh, Assam, India
  • Dipjyoti Sarma  Department of Mathematics, NKD Jr. College, Tinsukia, Assam, India

Keywords:

Keywords: Triangular fuzzy number, Gaussian fuzzy number, linear system of fuzzy version, uncertainty

Abstract

ABSTRACT: With uncertainty on the parameters, linear system of equations plays an important role in Economics and Finance. In Economics, linear systems of equations with uncertainty on parameters are widely used due to some imprecise data on the relation of linear system of equations. In this paper, an economic problem is solved by fuzzy version of linear system of equations.

References

  1. Amirfakhrian, M. (2007). Numerical solution of fuzzy system of linear equations with polynomial parametric form, International Journal of Computer Mathematics, Vol. 84, pp. 1089-1097.
  2. Amirfakhrian, M. (2012). Analyzing the solution of a sustem of fuzzy linear equations by a fuzzy distance, Soft Computing, Vol. 16, pp. 1035-1041.
  3. Asady, B., Abbasbandy, S. and Alavi, M. (2005). Fuzzy general linear systems, Applied Mathematics and Computation, Vol. 169, pp. 34-40.
  4. Behera, Diptiranjan and Chakraverty, S. (2012). A new method for solving real and complex fuzzy system of linear equations, Computational Mathematics and Modeling, Vol. 23, pp. 507-518.
  5. Buckley, J.J., Solving fuzzy equations in economics and finance, Fuzzy Sets and Systems, v. 48 n. 3, p. 289-296, 1992.
  6. Buckley, J.J., The fuzzy mathematics of finance, Fuzzy Sets and Systems, v.21 n.3, p. 257-273, 1987.
  7. Calzi, M.L., Towards a general setting for the fuzzy mathematics of finance, Fuzzy Sets and Systems, v. 35 n.3, p.265-280, 1990.
  8. Chakraverty, S. and Behera, Diptiranjan (2012). Fuzzy system of linear equations with crisp coefficients , Journal of Intelligent and Fuzzy Systems, DOI : 10.3233/IFS-2012-0627.
  9. Chiu, C-Y., Park, C.S., “Fuzzy Cash Flow Analysis Using Present Worth Criterion,” The Engineering Economist, 39, (2), pp. 113-138, 1994.
  10. Cong-Xing, W. and Ming, M. (1991). Embedding problems of fuzzy number space : part I, Fuzzy Sets and Systems, Vol. 44, pp. 33-38.
  11. Das, S. and Chakraverty, S. (2012). Numerical solution of interval and fuzzy system of linear equations, Applications and Applied Mathematics: An International Journal (AAM), Vol. 7, pp. 334-356.
  12. Dimitrovski, A.D., Matos, M.A., Fuzzy engineering economic analysis, IEEE Transactions  on Power Systems, Vol. 15, No. 1, pp.283-289, 2000.
  13. Friedman, M., Ming, M. and Kandel, A. (1991). Fuzzy linear systems, Fuzzy sets and systems, Vol. 96, pp. 201-209.
  14. Garg, Anjeli and Singh, S.R. (2008). Solving fuzzy system of equations using Gaussian membership function, International Journal of Computational Cognition, Vol. 7, pp. 25-32.
  15. Horcik, R. (2008). Solution of a system of linear equations with fuzzy numbers, Fuzzy and Systems, Vol. 159, pp. 1788-1810.
  16. Kahraman, C., Fuzzy versus probabilistic benefit/cost ratio analysis for public work projects, Int. J. Appl. Math. Comp. Sci., v. 11, N. 3, pp.705-718, 2001.
  17. Kahraman, C. Tolga, E., Ulukan, Z., Justification of manufacturing technologies using fuzzy benefit/cost ratio analysis, International Journal of Production Economics, 66(1), pp.45-52, 2000.
  18. Kahraman, C., Ulukan, Z., Gulbay, M., Investment analyses under fuzziness using possibilities of probabilities, Proceedings, Vol. III, pp. 1721-1724, 11th IFSA World Congress, 2005, Beijing, China.
  19. Li, J., Li, W. and Kong, X. (2010), A new alogrithm model for solving fuzzy linear systems, Southest Asian Bulletin of Mathematics, Vol. 34, pp. 121-132.
  20. Liou, T-S., Chen, C-W., Fuzzy Decision Analysis for Alternative Selection Using a Fuzzy Annual Worth Criterion, The Engineering Economist: A Journal Devoted to the Problems of Capital Investment, Volume 51, Issue 1, 2006, Pages 19-34.
  21. Omitaoumu, O.A., Badiru, A., Fuzzy Present Value Analysis Model For Evaluating Information System Projects, The Engineering Economicst: A Journal Devoted to the Problems of Capital Investment, Volume 52, Issue 2, 2007, Pages 157-178.
  22. Senthilkurama, P. and Rajendran, G., (2011). An algorithmic approach to solve fuzzy linear Systems, Journal of Information & Computational Science, Vol. 8, pp. 503-510.
  23. Senthilkurama, P. and Rajendran, G., (2011). New approach to solve symmetric fully fuzzy linear systems, Sadhana, Vol. 36, pp. 933-940.
  24.  Sevastjanov, P. and Dymova, L. (2009). A new method for solving interval and fuzzy equations: linear case, Information Sciences, Vol. 179, pp. 925-937.
  25. Vroman, A., Deschrijver, G. and Kerre, E.E. (2007). Solving system of linear fuzzy equations by parametric functions, IEEE Transaction on Fuzzy Systems, Vol. 15, pp. 370-384.
  26. Wang, X., Zhong, Z. and Ha, M. (2001). Iteration alogrithms for solving a system of fuzzy linear equations, Fuzzy Sets and Systems, Vol. 119, pp. 121-128.

International Journal of Scientific Research in Science, Engineering and Technology

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Published

2015-12-30

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Volume 1, Issue 6, November-December-2015

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Research Articles

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How to Cite

[1]
Rupjit Saikia, Dipjyoti Sarma, " A Case study on an Economic problem by using Fuzzy linear Equations, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 1, Issue 6, pp.391-394, November-December-2015.