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%).


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    Title :

    Genetic Algorithm: Application to Scattered Data Problems using Lipschitz Interpolation


    Contributors:


    Publication date :

    2008-07-01


    Size :

    3509765 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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