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

Q. Long, M. Xie, S. H. Ng, Gregory Levitin

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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. © 2007 Elsevier B.V. All rights reserved.
Original languageEnglish
Pages (from-to)238-250
JournalEuropean Journal of Operational Research
Volume191
Issue number1
DOIs
Publication statusPublished - 16 Nov 2008
Externally publishedYes

Research Keywords

  • Genetic Algorithms (GA)
  • Reliability analysis
  • Reliability optimization
  • Weighted voting systems (WVS)

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