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In this paper, a low computational method of efficiently and quickly handling large multivariate scattered data sets with a genetic algorithm for design parameter optimization is presented. The method presented combines the use of a genetic algorithm and the linear interpolation technique identified as Lipschitz Interpolation. Using this method we have improved the performance of the algorithm in two ways, the variance of the solution and the total algorithm evaluation time (an improvement of magnitude 90%).
Date of Conference: 16-18 July 2008