Application of Adaptive Particle Swarm Optimization Algorithm

The Adaptive Particle Swarm Optimization Algorithm Application is an optimization technique based on the particle swarm algorithm, capable of solving various computational problems. This MATLAB-implemented application provides an excellent starting point for beginners, featuring clear code organization with modular functions for particle initialization, velocity updates, and fitness evaluation. Through the adaptive PSO implementation, users can optimize objective functions using dynamic parameter adjustment mechanisms that automatically tune inertia weights and acceleration coefficients based on swarm diversity. The application includes built-in visualization tools that plot convergence curves and particle movement patterns, allowing users to observe optimization progress in real-time. With its intuitive interface design containing preset benchmark functions and parameter configuration panels, beginners can easily comprehend and apply adaptive PSO fundamentals. This implementation enables quick mastery of core algorithm concepts including global-best and personal-best position updates, boundary handling methods, and termination criteria implementation.