CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Fuzzy Approach to Replacement Problem with Value of Money Changes with Time

by Pranab Biswas, Surapati Pramanik
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 30 - Number 10
Year of Publication: 2011
Authors: Pranab Biswas, Surapati Pramanik
10.5120/3676-5151

Pranab Biswas, Surapati Pramanik . Fuzzy Approach to Replacement Problem with Value of Money Changes with Time. International Journal of Computer Applications. 30, 10 ( September 2011), 28-33. DOI=10.5120/3676-5151

@article{ 10.5120/3676-5151,
author = { Pranab Biswas, Surapati Pramanik },
title = { Fuzzy Approach to Replacement Problem with Value of Money Changes with Time },
journal = { International Journal of Computer Applications },
issue_date = { September 2011 },
volume = { 30 },
number = { 10 },
month = { September },
year = { 2011 },
issn = { 0975-8887 },
pages = { 28-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume30/number10/3676-5151/ },
doi = { 10.5120/3676-5151 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:16:43.891762+05:30
%A Pranab Biswas
%A Surapati Pramanik
%T Fuzzy Approach to Replacement Problem with Value of Money Changes with Time
%J International Journal of Computer Applications
%@ 0975-8887
%V 30
%N 10
%P 28-33
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Fuzzy set has been applied in many real applications to handle uncertainty. The aim of the paper is to study the replacement problem with uncertainty. This problem involves capital cost, scrap value or salvage value, maintenance cost or operating cost, and rate of interest having an imprecise value. Here, we assume the imprecise values as positive trapezoidal fuzzy numbers. Moreover, we consider that the value of money changes with fuzzy rate of interest due to market fluctuations. To deal with this type of problem, we first find out the present worth value of money and then determine the fuzzy annualized costs. By using Yager’s ranking method, comparison of fuzzy annualized costs is done to obtain an optimal replacement policy. Numerical example is provided to check the validity of the proposed method.

References
  1. Bellman, R.E., 1955. Equipment replacement policy. SIAM Journal Applied Mathematics 3,133-136.
  2. Alchian, A.A.1952. Economic Replacement Policy. Technical Report Publication R-224. The RAND Corporation, Santa Monica, CA.
  3. Dreyfus, S.E., and Law, A.M. 1977. The Art and Theory of Dynamic Programming. Academic Press, New York.
  4. Ohnishi, M.1997. Optimal minimal- repair and replacement problem under average cost criterion: optimality of (t, T) policy. Journal of the Operations Research Society of Japan 40(3), Sept.
  5. Dimitrakos, T.D., and Kyriakidis, E.G. 2007. An improved algorithm for the computation of the optimal repair/replacement policy under general repairs. European Journal of Operational Research 182, 775–782
  6. Mahdavi, M., and Mahdavi, M. 2009. Optimization of age replacement policy using reliability based heuristic model. Journal of Scientific & Industrial Research 68, 668-673.
  7. Zhao, X. F., Chen, M., Nakagawa, T. 2010. Three kinds of replacement models combined with additive and independent damages. In Proceedings of the Ninth International Symposium on Operations Research and Its Applications (ISORA’10), 31–38.
  8. Nezhad, M. S. F., Niaki, S. T. A., Jahromi, A. E. 2007. A One-stage two-machine replacement strategy based on the Bayesian inference method. Journal of Industrial and Systems Engineering 1(3), 235-250.
  9. Von Neumann, J., and Morgenstern, O. 1944. Theory of Games and Economic Behavior. Princeton University Press, Princeton, NJ.
  10. Zadeh, L.A. 1965. Fuzzy sets, Information and Control 8, 338-352.
  11. Buckley, J. 1987. The fuzzy mathematics of finance. Fuzzy Sets and Systems 21, 257-273.
  12. Buckley, J. 1992. Solving fuzzy equations in economics and finance. Fuzzy Sets and Systems 48, 289-296.
  13. Choobineh, F., and Behrens, A. 1992. Use of intervals and possibility distributions in economic analysis. Journal of the Operational Research Society 43(9), 907-918.
  14. Ward, T. 1985. Discounted fuzzy cash flow analysis. In Proceedings of the 1985 Fall Industrial Engineering Conference, 476-481.
  15. Chiu, C., and Park, C. 1994. Fuzzy cash flow analysis using present worth criterion. The Engineering Economist 39(2), 113-138.
  16. Biswas, P., and Pramanik, S. 2011. Application of fuzzy ranking method to determine the replacement time for fuzzy replacement problem. International Journal of Computer Applications (July 2011), 25(11), 41-47.
  17. Yager, R.R. 1981. A procedure for ordering fuzzy subsets of the unit interval. Information Sciences 24, 143-161
  18. Dubois, D., and Prade, H. 1980. Fuzzy Sets and Systems: Theory and Applications. Academic Press, New York.
  19. Dubois, D., and Prade, H. 1978. Operations on fuzzy numbers. International Journal of Systems Science 9, 612-626.
  20. Dubois, D., and Prade, H. 1987. Fuzzy numbers: an overview. In Bezdek, J., editor, Analysis of Fuzzy Information, 1, 3-39. CRC Press, Boca Raton, FL.
  21. Kauffmann, A., and Gupta, M. 1991. Introduction to fuzzy Arithmetic: Theory and Applications. Van Nostrand Reinhold, New York.
  22. Bansal, A. 2011. Trapezoidal fuzzy number (a, b, c, d): arithmetic behavior. International Journal of Physical and Mathematical Sciences, 39-44.
  23. Klir, G. and Yuan, B. 1995. Fuzzy Sets and Fuzzy Logic: Theory and Applications. Prentice Hall PTR, Upper River Saddle, NJ.
  24. Zadeh, L. A. 1978. Fuzzy sets as a basis for a theory of possibility. IEEE Transactions on Systems, Man, and Cybernetics 1, 3-28.
  25. Zimmerman, H. 1991. Fuzzy Set Theory and Its Applications. Kluwer Academic Press, Boston, MA, second edition.
  26. Karsak, E. E., and Tolga, E. 2001. Fuzzy multi-criteria decision-making procedure for evaluating advanced manufacturing system investments. Int. J. Production Economics 69, 49-64.
Index Terms

Computer Science
Information Sciences

Keywords

Fuzzy sets Fuzzy replacement problem Replacement time Trapezoidal fuzzy number

Powered by PhDFocusTM