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Reliability analysis and optimization of weighted voting systems with continuous states input

Author

Listed:
  • Long, Q.
  • Xie, M.
  • Ng, S.H.
  • Levitin, Gregory

Abstract

Weighted voting systems are widely used in many practical fields such as target detection, human organization, pattern recognition, etc. In this paper, a new model for weighted voting systems with continuous state inputs is formulated. We derive the analytical expression for the reliability of the entire system under certain distribution assumptions. A more general Monte Carlo algorithm is also given to numerically analyze the model and evaluate the reliability. This paper further proposes a reliability optimization problem of weighted voting systems under cost constraints. A genetic algorithm is introduced and applied as the optimization technique for the model formulated. A numerical example is then presented to illustrate the ideas.

Suggested Citation

  • Long, Q. & Xie, M. & Ng, S.H. & Levitin, Gregory, 2008. "Reliability analysis and optimization of weighted voting systems with continuous states input," European Journal of Operational Research, Elsevier, vol. 191(1), pages 240-252, November.
    • Handle: RePEc:eee:ejores:v:191:y:2008:i:1:p:240-252
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    References listed on IDEAS

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    1. Levitin, Gregory & Xie, Min & Zhang, Tieling, 2007. "Reliability of fault-tolerant systems with parallel task processing," European Journal of Operational Research, Elsevier, vol. 177(1), pages 420-430, February.
    2. Gregory Levitin, 2005. "The Universal Generating Function in Reliability Analysis and Optimization," Springer Series in Reliability Engineering, Springer, number 978-1-84628-245-4, September.
    3. Levitin, Gregory, 2002. "Evaluating correct classification probability for weighted voting classifiers with plurality voting," European Journal of Operational Research, Elsevier, vol. 141(3), pages 596-607, September.
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    Cited by:

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    5. Wang, Yong & Li, Lin & Huang, Shuhong & Chang, Qing, 2012. "Reliability and covariance estimation of weighted k-out-of-n multi-state systems," European Journal of Operational Research, Elsevier, vol. 221(1), pages 138-147.
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