Function Optimization Using Genetic Algorithm
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This MATLAB-implemented genetic algorithm program provides a comprehensive solution for various optimization problems. Genetic algorithms simulate natural evolutionary processes by implementing genetic operations such as selection, crossover, and mutation to search for optimal solutions. The program includes key functions for population initialization, fitness evaluation, tournament selection, uniform crossover, and Gaussian mutation. Users can easily configure parameters like population size, crossover rate, mutation rate, and termination criteria. The implementation features elite preservation strategy to maintain best solutions across generations and includes visualization tools for monitoring convergence progress. This tool enables efficient function optimization in MATLAB environment, delivering optimal results through biologically-inspired computational methods.
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