MATLAB Implementation of Artificial Fish Swarm Algorithm

This MATLAB implementation demonstrates the Artificial Fish Swarm Algorithm (AFSA), an intelligent optimization technique that simulates fish schooling behavior to solve complex optimization problems. The algorithm mimics natural fish behaviors including prey searching, swarming, and following to iteratively search for optimal solutions through position and behavior adjustments. Key implementation features include: - Fish movement simulation with visual distance and step size parameters - Prey behavior implementation using fitness evaluation functions - Swarming behavior with center position calculations - Following mechanism that tracks optimal neighbors - Random behavior for exploration diversity The algorithm's extensive applicability spans engineering optimization, data mining, and artificial intelligence domains. Mastering AFSA significantly enhances problem-solving capabilities and algorithm design skills through practical MATLAB coding experience. This comprehensive implementation provides complete code structure, parameter configuration examples, and detailed comments, making it an excellent resource for both learning and practical applications. I strongly recommend studying and bookmarking this thorough MATLAB implementation for its educational value and real-world optimization utility.