Genetic Algorithm Implementation Using MATLAB
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Resource Overview
A MATLAB-based genetic algorithm program with comprehensive code documentation, featuring clear algorithm explanations and function descriptions for easy understanding and implementation.
Detailed Documentation
This genetic algorithm program is implemented using MATLAB programming language. The implementation includes key genetic algorithm components such as population initialization, fitness evaluation, selection (using tournament or roulette wheel selection), crossover (single-point or multi-point crossover), and mutation operations. The code structure follows standard genetic algorithm workflow: creating initial population, evaluating fitness, selecting parents, performing crossover and mutation to generate new offspring, and iterating until convergence criteria are met. Each function is well-documented with comments explaining parameters and return values, making it accessible for both beginners and experienced MATLAB users. The algorithm can be easily adapted for various optimization problems by modifying the fitness function and parameter settings.
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