Fundamental PSO Implementation and Three Classic Improved Algorithms

This package contains comprehensive MATLAB implementations of the fundamental Particle Swarm Optimization algorithm along with three classical improved variants: GPSO (Generalized PSO), ARPSO (Adaptive Randomized PSO), and HPSO (Hybrid PSO). These enhanced algorithms represent significant modifications developed by researchers to optimize convergence speed, solution quality, and avoidance of local optima through sophisticated parameter adaptation mechanisms and hybrid optimization strategies. The codebase features modular architecture with clear separation between core PSO components and improvement modules. Key implementation aspects include: - Velocity update functions with inertial weight adjustments - Position boundary handling mechanisms - Fitness evaluation interfaces for easy customization - Adaptive parameter tuning modules for ARPSO - Hybrid operator implementations in HPSO While the original research papers detailing the theoretical foundations of these improved algorithms are not included in this distribution, researchers are encouraged to download them from academic databases for deeper understanding of the mathematical principles and performance advantages. These papers provide valuable insights into the convergence analysis and comparative performance metrics that informed our code implementation decisions. The implementations maintain consistent function naming conventions and parameter structures across all variants, facilitating easy comparison and modification. Each algorithm includes demonstration scripts showing basic usage patterns and performance visualization capabilities.