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

Quan Long*, M. Xie, S. H. Ng, Gregory Levitin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

21 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)240-252
Number of pages13
JournalEuropean Journal of Operational Research
Volume191
Issue number1
DOIs
StatePublished - Nov 16 2008

Keywords

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

ASJC Scopus subject areas

  • Computer Science(all)
  • Modeling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management

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