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

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

22 Scopus Citations
View graph of relations

Author(s)

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

Detail(s)

Original languageEnglish
Pages (from-to)238-250
Journal / PublicationEuropean Journal of Operational Research
Volume191
Issue number1
Publication statusPublished - 16 Nov 2008
Externally publishedYes

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.

Research Area(s)

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