Artificial Fish Swarm Algorithm MATLAB Implementation
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Resource Overview
This MATLAB implementation of the Artificial Fish Swarm Algorithm provides a practical demonstration of the algorithm's optimization capabilities, featuring comprehensive code structure with key functions for fish behavior simulation, including prey(), swarm(), follow(), and move() operations.
Detailed Documentation
This algorithm represents a MATLAB implementation of the Artificial Fish Swarm Algorithm (AFSA), which solves optimization problems by simulating the collective behavior of fish swarms. As a heuristic optimization technique, AFSA finds applications across various domains such as engineering design and intelligent optimization systems. The implementation includes core algorithmic components like visual distance calculation, crowding factor adjustment, and step size control mechanisms. Through this MATLAB code, users can gain deep insights into AFSA's fundamental principles and practical applications, with detailed comments explaining parameter tuning and convergence criteria. This implementation serves as a valuable resource for effectively applying artificial fish swarm algorithms to solve real-world optimization challenges while providing modifiable code structure for custom adaptations.
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