A PSO-based bacterial chemotaxis algorithm and its application

Authors:
Rui Zhang;Jianzhong Zhou;Youlin Lu;Hui Qin;Huifeng Zhang
Affiliations:
Collage of Hydorpower Information Engineering, Huazhong University of Scence and Technology, Hubei, China;Collage of Hydorpower Information Engineering, Huazhong University of Scence and Technology, Hubei, China;Collage of Hydorpower Information Engineering, Huazhong University of Scence and Technology, Hubei, China;Collage of Hydorpower Information Engineering, Huazhong University of Scence and Technology, Hubei, China;Collage of Hydorpower Information Engineering, Huazhong University of Scence and Technology, Hubei, China
Venue:
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part III
Year:
2011

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Abstract

In this paper, a new two-phased optimization algorithm called BC-PSO is presented. Bacterial Chemotaxis Algorithm is a biologically inspired optimization method which is analyzing the way bacteria react to chemoattractants in concentration gradients. Aiming at the shortcomings of BC which is lack of global searching ability with low speed, PSO is introduced to accelerate convergence before BC works. With some famous test functions been used, the numerical experiment results and comparative analysis prove that it outperforms standard PSO and GA. Finally, the hybrid algorithm is applied to solve the problem of mid-long term optimal operation of cascade hydropower stations. Comparing with the other algorithms, the operation strategy shows its higher efficiency.