Bacterial Particle Swarm Optimization Algorithm

Abstract:

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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.

Info:

Periodical:

Advanced Materials Research (Volumes 211-212)

Edited by:

Ran Chen

Pages:

968-972

DOI:

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

Citation:

M. Li and X. L. Ji, "Bacterial Particle Swarm Optimization Algorithm", Advanced Materials Research, Vols. 211-212, pp. 968-972, 2011

Online since:

February 2011

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Price:

$35.00

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