Guaranteed Convergence Particle Swarm Optimization (GCPSO)

The Guaranteed Convergence Particle Swarm Optimization (GCPSO) is an advanced variant of the classical Particle Swarm Optimization (PSO).

The Guaranteed Convergence Particle Swarm Optimization (GCPSO) is an advanced variant of the classical Particle Swarm Optimization (PSO) algorithm, designed to improve convergence towards optimal solutions in complex optimization problems. The key feature of GCPSO is its ability to guarantee local convergence by incorporating a constriction coefficient that dynamically adjusts particle velocities, ensuring a more controlled and stable search process. Additionally, GCPSO includes mechanisms to adapt particle movement based on successes and failures during optimization, such as updating a perturbation scaling factor to adjust search intensity. This helps the algorithm avoid premature convergence and escape local optima by modulating particle exploration and exploitation. Overall, GCPSO is well-suited for high-dimensional and multi-modal optimization tasks, providing a robust balance between global search capabilities and local refinement.

Some articles that have used this algorithm:

https://doi.org/10.1109/JPHOTOV.2024.3414115

https://doi.org/10.18618/REP.2005.1.063070

https://doi.org/10.1109/WCNPS60622.2023.10344974