A PCA-GA approach for weighted voting system optimization based on reliability, cost and system output analyses

The objective of this paper is to present a model for optimization of weighted voting systems (WVS). To achieve this objective, a comprehensive study was conducted to recognize economic and technical indicators (indices) which have great influences upon system performance. These indicators are related to components¿ reliability, operation costs, repair and maintenance costs and total expected output. Principal component analysis (PCA) is employed to provide insight on the importance of performance indices and to determine their weights. We formulate the problem of finding structure of parallel WVS (including choice of system elements) in order to achieve a desired level of system output by the minimal cost and maximum reliability. A genetic algorithm is introduced and applied as the optimization technique for the model formulated. A numerical example is presented to illustrate the ideas.