Uncertainty Approaches for Solving Generalized Machine Maintenance Problem

##plugins.themes.bootstrap3.article.main##

  •   Samir Abdou Abass

  •   Asmaa S. Abdallah

  •   Marwa Shehata Elsayed

  •   Eman Massoud Ahmed

Abstract

In this paper, the generalized machine maintenance problem is formulated as linear programming model. The objective is to maximize the percentage production hours available per maintenance cycle of each machine.  Data in many real life engineering and economic problems suffers from inexactness. There are different approaches to deal with uncertain optimization problems. In this paper two different approaches of uncertainty, Fuzzy programming and rough interval programming approaches will be introduced. We deal the concerned problem with uncertain data in coefficients of the constraints for the two approaches. A numerical example is introduced to clarify the two proposed approaches. A comparison study between the obtained results of the two proposed approaches and the results of interval approach for Samir A. and Marwa Sh [3] will be introduced.


Keywords: Machine Maintenance Problem, Fuzzy Programming, Rough Interval Programming, Linear Programming

References

A. Samir. Abass, and Sh. Marwa Elsayed, "Genearlized machine maintenance problem under uncertainty," International journal of Research in Management, vol. 4, no. 2, pp.77-86, 2012.

M. Allan, K. Lockyer, and J. Oakland, Production and Operation Management, Pitman Publishing Company London, pp. 421, 1988.

P. Joseph, Productivity Management, Allyn and Bacon Inc. Massachusetts, (1987).

B. Kareem, and A.A. Aderoba, "Linear programming based effective Maintenance and manpower planning strategy: A case study," International journal of the computer, the internet and management, vol. 16, no. 2, pp. 26-34, 2008.

J. Galbraith, Designing Complex Organizations, Addison Wesley Reading, Massachusetts: Addison Wesley, 1973.

R. E. Bellman, and L. A. Zadeh, " Decision-Making in a Fuzzy Environment," Management Science, vol. 17, no. 4, pp. 141-273, 1970.

H. Tanaka, T. Okuda, and K. Asai, "On fuzzy mathematical programming," Journal of cybernetics, vol. 3, pp. 36-47, 1974.

H.J. Zimmermann, "Fuzzy programming and linear programming with several objective functions," Fuzzy Sets and Systems, vol. 1, pp. 45–55, 1978.

A. Ebrahimnejad, S.H. Nasseri, and F. Hosseinzadeh Lotfi, "Bounded linear programs with trapezoidal fuzzy numbers," International Journal of Uncertainty,Fuzziness and Knowledge-Based Systems, vol. 18, no. 3, pp. 269–286, 2010.

H.R. Maleki, M. Tata, and M. Mashinchi, "Linear programming with fuzzy variables," Fuzzy Sets and Systems, vol. 109, pp. 21–33, 2000.

Z. Pawlak, "Rough sets," International Journal of Information and Computer Sciences, vol. 11, no 5, pp. 341–356, 1982.

I. Düntsch, and G., Gediga, "Rough set dependency analysis in evaluation studies: An application in the study of repeated heart attacks," Informatics research report 10, university of Ulster, pp. 25-30, 1995.

J. Krysinski, "Rough sets in the analysis of the structure-activity relationships of antifungal imidazolium compounds," Journal of Pharmaceutical Sciences, vol. 84, no. 2, pp. 243–248, 1995.

Y. Weiguo, L. Mingyu, and L. Zhi, "Variable precision rough set based decision tree classifier," Journal of Intelligent and Fuzzy Systems, vol. 23, no. 2, pp. 61–70, 2012.

M. Arabani, and M.A.L. Nashaei, "Application of Rough Set theory as a new approach to simplify dams location," Scientia Iranica, vol. 13, no. 2, pp. 152–158, 2006.

M.S. Osman, E.F. Lashein, E.A. Youness, and T.E.M. Atteya, "Mathematical programming in rough environment," Optimisation, vol. 60, no. 5, pp. 603–611, 2011.

E.A. Youness, "Characterizing solutions of rough programming problems," European Journal of Operational Research, vol. 168, no. 3, pp. 1019–1029, 2006.

A. Hamzeheea, M. A. Yaghoobia, and M. Mashinchib, "Linear programming with rough interval Coefficients," Journal of Intelligent & Fuzzy Systems, vol. 26, pp. 1179–1189, 2014.

Downloads

Download data is not yet available.

##plugins.themes.bootstrap3.article.details##

How to Cite
[1]
Abass, S., Abdallah, A., Elsayed, M. and Ahmed, E. 2020. Uncertainty Approaches for Solving Generalized Machine Maintenance Problem. European Journal of Engineering Research and Science. 5, 6 (Jun. 2020), 675-682. DOI:https://doi.org/10.24018/ejers.2020.5.6.1813.