Explore MATLAB source code curated for "人工鱼群算法" with clean implementations, documentation, and examples.
The Artificial Fish Swarm Algorithm is an autonomous optimization paradigm inspired by aquatic collective behavior, designed to solve complex problems through decentralized decision-making and local interactions.
An excellently written implementation of the artificial fish swarm algorithm, ideal for beginners with code examples and detailed explanations.
This repository contains MATLAB code implementing the Artificial Fish Swarm Algorithm (AFSA) used in my academic thesis. The code demonstrates optimization problem-solving capabilities and includes detailed algorithm analysis for practical applications.
Complete source code implementation of Artificial Fish Swarm Algorithm using MATLAB, featuring optimization functions, swarm intelligence parameters, and benchmark testing capabilities for educational purposes.
Implementation of Artificial Fish Swarm Algorithm to solve the Traveling Salesman Problem - Currently the only available online implementation, personally developed with guaranteed successful convergence
Implementation of Artificial Fish Swarm Algorithm for IEEE Power System Planning Applications
A comprehensive MATLAB implementation comparing Particle Swarm Optimization (PSO) and Artificial Fish Swarm Algorithm (AFSA), demonstrating their respective advantages and limitations through performance analysis and application scenarios
Implementation of Artificial Fish Swarm Algorithm for solving path planning problems, including main function and relevant subfunctions with complete code structure.
Implementation of Artificial Fish Swarm Algorithm for Cascade Reservoir Optimization Scheduling with Code Integration
Artificial Fish Swarm Algorithm for Solving Multidimensional Complex Optimization Problems