A particle swarm optimization algorithm with dynamic weights

Junhui Lu; Lü Zhang; Yuntao Yue

doi:10.1117/12.2685758

15 August 2023 A particle swarm optimization algorithm with dynamic weights

Junhui Lu, Lü Zhang, Yuntao Yue

Proceedings Volume 12719, Second International Conference on Electronic Information Technology (EIT 2023); 127194I (2023) https://doi.org/10.1117/12.2685758
Event: Second International Conference on Electronic Information Technology (EIT 2023), 2023, Wuhan, China

Abstract

Particle swarm optimization algorithm is a stochastic global optimization algorithm, inertia weight is one of its important parameters, in order to improve its easy to fall into the defects of local optimization and precocious maturity, this paper proposes a new dynamic weight particle swarm optimization algorithm. The new algorithm designs a dynamic weight based on the global optimal solution and its own optimal solution, which makes the velocity change of particles more reasonable, applies it to the classical test function, accelerates the convergence speed, and effectively improves the difficulty of falling into local optimum, and improves the global search ability.

Citation Download Citation

Junhui Lu, Lü Zhang, and Yuntao Yue "A particle swarm optimization algorithm with dynamic weights", Proc. SPIE 12719, Second International Conference on Electronic Information Technology (EIT 2023), 127194I (15 August 2023); https://doi.org/10.1117/12.2685758

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