What are some common issues with PSO?
Common issues with Particle Swarm Optimization (PSO) include premature convergence, sensitivity to parameters, and local optima.
Can you explain premature convergence?
Premature convergence occurs when the swarm settles on a suboptimal solution too early, preventing exploration of better solutions.
How can I avoid these issues in my PSO implementation?
To avoid these issues, you can adjust parameters like inertia weight, use diverse initial populations, or implement hybrid approaches.
Are there any specific applications where PSO struggles?
Yes, PSO can struggle in high-dimensional spaces or when the objective function is highly complex and multimodal.
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