Comparison of fitness scaling functions in genetic algorithms with applications to optical processing

Farzad Sadjadi

doi:10.1117/12.563910

22 October 2004 Comparison of fitness scaling functions in genetic algorithms with applications to optical processing

Farzad Sadjadi

Proceedings Volume 5557, Optical Information Systems II; (2004) https://doi.org/10.1117/12.563910
Event: Optical Science and Technology, the SPIE 49th Annual Meeting, 2004, Denver, Colorado, United States

Abstract

Many optical or image processing tasks reduce to the optimization of some set of parameters. Genetic algorithms can optimize these parameters even when the functions they map are fairly complicated, but they can only do so the point where the fitness functions they are given can differentiate between good results and the best result. This can occur when the optimal point is in a region (in a three dimensional example) such as a plateau, where all the surrounding points are of very nearly the same fitness. If there are multiple peaks in close proximity, all of nearly the same fitness but with very deep divides, the algorithm will have trouble 'hopping' from one to the other. One way to overcome these obstacles is to scale the fitness values given by the fitness function, thereby gently modifying the fitness function from the point of view of the algorithm, thus rewarding the more fit solutions to a higher precision than would naturally occur. Four such scaling methods will be compared based upon their handling of a sample set of optical processing data. Success will be determined by comparing the variance over time, selection pressure over time, and best of generation graphs.

Citation Download Citation

Farzad Sadjadi "Comparison of fitness scaling functions in genetic algorithms with applications to optical processing", Proc. SPIE 5557, Optical Information Systems II, (22 October 2004); https://doi.org/10.1117/12.563910

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