Bacterial Particle Swarm Optimization Algorithm

Ming Li; Xue Ling Ji

doi:10.4028/www.scientific.net/AMR.211-212.968

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 211-212Bacterial Particle Swarm Optimization Algorithm

Bacterial Particle Swarm Optimization Algorithm

Abstract:

The loss of the population diversity leads to the premature convergence in existing particle swarm optimization(PSO) algorithm. In order to solve this problem, a novel version of PSO algorithm called bacterial PSO(BacPSO), was proposed in this paper. In the new algorithm, the individuals were replaced by bacterial, and a new evolutionary mechanism was designed by the basic law of evolution of bacterial colony. Such evolutionary mechanism also generated a new natural termination criterion. Propagation and death operators were used to keep the population diversity of BacPSO. The simulation results show that BacPSO algorithm not only significantly improves convergence speed ,but also can converge to the global optimum.

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Periodical:

Advanced Materials Research (Volumes 211-212)

Pages:

968-972

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.211-212.968

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Online since:

February 2011

Authors:

Ming Li, Xue Ling Ji

Keywords:

Bacterial Individual, Evolutionary Mechanism, Global Optimum, PSO Algorithm

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References

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