13 Commonly Used Particle Swarm Optimization Algorithms
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Resource Overview
This collection includes 13 different particle swarm optimization algorithms that are all executable, featuring implementation approaches like velocity update mechanisms and position boundary handling. Each algorithm comes with straightforward MATLAB code demonstrating key functions such as fitness evaluation and swarm initialization, making it easy to read and modify according to your specific optimization needs.
Detailed Documentation
This article presents 13 commonly used particle swarm optimization algorithms, each fully functional and ready for implementation. If you're searching for a specific variant, you've come to the right place! The algorithms feature clean code structure with clearly defined components including inertia weight adjustment methods, social and cognitive parameter tuning, and convergence criteria implementation. All code is highly readable with proper commenting, allowing you to download and customize the algorithms easily for your experimental or project requirements. These optimization techniques will prove invaluable for solving complex problems in engineering, data analysis, and computational intelligence applications.
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