MATLAB Implementation of Adaptive Particle Swarm Optimization (APSO) Algorithm

We have developed an improved MATLAB implementation of Particle Swarm Optimization (APSO) by incorporating adaptive weight adjustment strategies. This enhanced algorithm not only maintains the collaborative search capabilities of traditional PSO but integrates adaptive weight features as a key improvement mechanism. The implementation includes dynamic weight updates based on swarm convergence behavior, allowing particles to better explore the solution space while adapting to problem-specific characteristics during the optimization process. The algorithm employs linear or non-linear weight reduction functions that automatically adjust inertia weights based on iteration progress and swarm diversity metrics. Key MATLAB functions include particle position updates with velocity clamping, fitness evaluation modules, and convergence monitoring routines. This improved algorithm demonstrates superior performance and accuracy when solving practical optimization problems. We provide complete MATLAB source code with detailed comments, making it suitable for researchers and practitioners working on complex optimization challenges.