Fish Swarm Algorithm for Function Optimization Code Implementation

Code implementation of function optimization algorithms based on fish swarm optimization technique. For detailed explanations and comprehensive tutorials, please refer to the included documentation. Due to file size limitations, contact me at 1066146635@qq.com for high-definition tutorial materials. The implementation includes key swarm intelligence components like fish behavior simulation, collective movement patterns, and fitness evaluation mechanisms.

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Function Optimization Using Genetic Algorithms and Nonlinear Programming

Function optimization based on genetic algorithms and nonlinear programming, featuring detailed algorithmic implementation explanations. Please contact me for high-resolution tutorials due to file size limitations.

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Function Optimization Using Penalty Function-Based Particle Swarm Algorithm

Since the establishment of bionics in the mid-1950s, researchers have begun developing bio-inspired algorithms to solve complex optimization problems. These algorithms simulate evolutionary mechanisms and include Simulated Annealing (SA), Seeker Optimization Algorithm (SOA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and Genetic Algorithms (GA). Notable contributions include Professor J.H. Holland's GA from University of Michigan, Rechenberg's Evolution Strategy, and Fogel's Evolutionary Programming.

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