Implementation of Artificial Fish Swarm Algorithm in Thesis Research

In my thesis research, I implemented the Artificial Fish Swarm Algorithm (AFSA) and developed corresponding MATLAB code. The algorithm demonstrates significant potential for optimization problems, particularly through its swarm intelligence approach simulating fish behaviors like preying, swarming, and following. The MATLAB implementation includes key functions for initialization, visual scope calculation, and behavior selection mechanisms. I provide detailed discussions on the algorithm's implementation aspects, including parameter tuning strategies and convergence analysis. The code structure features modular design with separate functions for different fish behaviors, making it adaptable for various optimization scenarios. Performance evaluation shows promising results in solving complex optimization challenges. For researchers interested in swarm intelligence algorithms, this implementation offers practical insights into AFSA's working mechanism and MATLAB coding techniques. The code includes comprehensive comments explaining critical operations such as distance calculations between artificial fish and fitness evaluation procedures. Should you have any questions regarding the algorithm implementation or suggestions for improvement, please feel free to contact me for further technical discussion.