Genetic Algorithm Implementation Based on gamultiobj
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Resource Overview
Optimizes dual-variable functions where multi_run serves as the main function and multi_fun acts as the fitness function. Parameter descriptions are available in comments, with additional performance tuning through parameter adjustments.
Detailed Documentation
This implementation provides optimization for dual-variable functions. The core structure consists of multi_run as the main execution function and multi_fun as the fitness evaluation function. Detailed parameter explanations can be found in the code comments. The algorithm utilizes MATLAB's gamultiobj function for multi-objective optimization, implementing genetic algorithm operations including selection, crossover, and mutation. Users can further enhance optimization performance by modifying parameters such as population size, generation count, and crossover rates. The fitness function multi_fun should be configured to return objective values for multi-objective evaluation.
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