Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/87197
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
Citation: 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
URI: http://scholarbank.nus.edu.sg/handle/10635/87197
ISSN: 03772217
Appears in Collections:Staff Publications

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