American Journal of Electrical and Electronic Engineering
ISSN (Print): 2328-7365 ISSN (Online): 2328-7357 Website: Editor-in-chief: Naima kaabouch
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American Journal of Electrical and Electronic Engineering. 2020, 8(1), 21-25
DOI: 10.12691/ajeee-8-1-3
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Research on Particle Swarm Optimization Algorithm Based on Quantum Computing Technology

Guanghui Wang1,

1Chinese Academy of Meteorological Sciences, Beijing 100081, China

Pub. Date: January 05, 2020

Cite this paper:
Guanghui Wang. Research on Particle Swarm Optimization Algorithm Based on Quantum Computing Technology. American Journal of Electrical and Electronic Engineering. 2020; 8(1):21-25. doi: 10.12691/ajeee-8-1-3


In view of the shortcomings of particle swarm optimization such as premature convergence to local optimization, particle swarm optimization algorithm based on quantum gate and particle swarm optimization algorithm based on quantum behavior are studied in this paper. The first algorithm uses the random observation method of quantum bit coding particles to simulate quantum particle collapse for generating a population and uses the quantum rotating gate to generate a new population. The adaptive mutation operator is used for ensuring the diversity of the population, effectively reducing the impact of local optimization; therefore, the robustness of the algorithm is improved. The second algorithm uses the probability density function of quantum computation to make the particles jump out of the local extreme points and fulfils the global search, which is more suitable for continuous optimization. The results of computational experiments show that both the two particle swarm optimization algorithms based on quantum technology have a good global convergence.

particle swarm optimization algorithm quantum gate quantum behavior quantum computation optimal value

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