• Mathematics
  • Published 2013

Effect of Defuzzification Methods in Redundancy Allocation Problem with Fuzzy Valued Reliabilities via Genetic Algorithm

@inproceedings{Mahato2013EffectOD,
  title={Effect of Defuzzification Methods in Redundancy Allocation Problem with Fuzzy Valued Reliabilities via Genetic Algorithm},
  author={Sanat Kumar Mahato and Laxminarayan Sahoo and Asoke Kumar Bhunia},
  year={2013}
}
This paper deals with redundancy allocation problem of complex system with ten subsystems connected in parallel with identical components. The reliability of each component is considered to be imprecise. This impreciseness has been represented by different fuzzy numbers. Then the corresponding problem has been transformed to crisp constrained optimization problem using different defuzzification methods. The transformed problem has been converted into unconstrained optimization problem by BigM… CONTINUE READING

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References

Publications referenced by this paper.
SHOWING 1-10 OF 43 REFERENCES

Genetic Algorithms: Search, Optimization and Machine Learning, Reading, MA

  • D. E. Goldberg
  • Addison Wesley,
  • 1989
VIEW 3 EXCERPTS
HIGHLY INFLUENTIAL

Effect of different defuzzification methods in a fuzzy based load balancing application

  • S. Nazz, A. Alam, R. Biswas
  • International Journal of Computer Science,
  • 2011

A Genetic Algorithm Based Reliability Redundancy Optimization for Interval valued Reliabilities of components

  • L. Sahoo, A. K. Bhunia, D. Roy
  • Journal of Applied Quantitative Methods,
  • 2010