Particle Swarm Optimization Algorithm Source Code with Technical Documentation

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Resource Overview

A valuable resource compiled by computational intelligence professors from Peking University's Computational Intelligence Laboratory, featuring complete PSO algorithm source code with detailed comments, supporting PPT documentation, and fifteen standard benchmark test functions for performance evaluation

Detailed Documentation

This comprehensive collection represents the diligent work of computational intelligence professors from Peking University's Computational Intelligence Laboratory. The materials include complete particle swarm optimization algorithm source code with thoroughly commented implementations, supporting PowerPoint documentation, and fifteen standardized test functions for algorithm validation. The code annotations provide clear explanations of key algorithm components including particle initialization, velocity update mechanisms using inertia weight and acceleration coefficients, and global/local best position tracking. The implementation demonstrates proper handling of boundary conditions and convergence criteria. These materials serve as excellent learning resources for PSO algorithms, with potential for expansion to include additional computational intelligence algorithms and educational materials to provide broader coverage of the field.

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