Adaptive Genetic Algorithm Implementation

MATLAB 967B 199 views 0 downloads 1 credits
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Resource Overview

MATLAB source code for adaptive genetic algorithm utilizing Gram-Schmidt orthogonalization decomposition. Users can alternatively implement QR decomposition for potential code simplification and computational efficiency improvements.

Detailed Documentation

This MATLAB implementation of an adaptive genetic algorithm employs Gram-Schmidt orthogonalization decomposition in its core processing. The algorithm dynamically adjusts crossover and mutation probabilities based on population fitness metrics. For alternative implementations, consider using QR decomposition which may offer computational advantages through built-in MATLAB functions like qr(). This substitution could potentially streamline the code structure while maintaining numerical stability. The genetic algorithm framework includes fitness evaluation, selection operators using roulette wheel or tournament methods, and adaptive parameter tuning mechanisms.

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