Title :
Genetic Algorithm: Application to Scattered Data Problems using Lipschitz Interpolation
Author :
Garbacik, Neil R. ; Zohdy, Mohammed A.
Author_Institution :
Sch. of Eng. & Comput. Sci., Oakland Univ., Rochester Hills, MI
Abstract :
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%).
Keywords :
genetic algorithms; interpolation; Lipschitz interpolation; design parameter optimization; genetic algorithm; linear interpolation; multivariate scattered data sets; scattered data problems; Algorithm design and analysis; Genetic algorithms; Genetic mutations; Interpolation; MATLAB; Mathematical model; Optimization methods; Particle scattering; Scattering parameters; Testing;
Conference_Titel :
Aerospace and Electronics Conference, 2008. NAECON 2008. IEEE National
Conference_Location :
Dayton, OH
Print_ISBN :
978-1-4244-2615-7
Electronic_ISBN :
7964-0977
DOI :
10.1109/NAECON.2008.4806516