Please use this identifier to cite or link to this item:
Title: Reliability analysis and optimization of weighted voting systems with continuous states input
Authors: Long, Q.
Xie, M. 
Ng, S.H. 
Levitin, G.
Keywords: Genetic Algorithms (GA)
Reliability analysis
Reliability optimization
Weighted voting systems (WVS)
Issue Date: 16-Nov-2008
Source: Long, Q., Xie, M., Ng, S.H., Levitin, G. (2008-11-16). Reliability analysis and optimization of weighted voting systems with continuous states input. European Journal of Operational Research 191 (1) : 238-250. ScholarBank@NUS Repository.
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.
Source Title: European Journal of Operational Research
ISSN: 03772217
DOI: 10.1016/j.ejor.2007.08.005
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.


checked on Feb 28, 2018


checked on Feb 20, 2018

Page view(s)

checked on Mar 12, 2018

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.