[1]Shang Zhigang,Wang Li,Li Mengmeng,et al.Improved Pigeon Herd Optimization Algorithm with Lost Exploration and Cluster Splitting Mechanism[J].Journal of Zhengzhou University (Engineering Science),2019,40(04):5-.[doi:10.13705/j.issn.1671-6833.2019.04.017]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
40
Number of periods:
2019 04
Page number:
5-
Column:
Public date:
2019-07-10
- Title:
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Improved Pigeon Herd Optimization Algorithm with Lost Exploration and Cluster Splitting Mechanism
- Author(s):
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Shang Zhigang 1; 2; 3; Wang Li 1; 2; Li Mengmeng 1; 2; Li Zhihui 1; 2; 3
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1. School of Electrical Engineering, Zhengzhou University; 2. Industrial Technology Research Institute, Zhengzhou University; 3. Henan Provincial Key Laboratory of Brain Science and Brain-Computer Interface Technology
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- Keywords:
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Pigeon flock optimization; get lost exploring; cluster split; global search; population diversity
- CLC:
-
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- DOI:
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10.13705/j.issn.1671-6833.2019.04.017
- Abstract:
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Pigeon inspired optimization (PIO) algorithm , as an emerging optimization technology, has the advantages of fast convergence and high precision. But it is not ideal for some problems with local optimal values. By introducing lost&exploration and c luster splitting mechanisms of natural flying pigeons, an improved PIO algorithm based on lost&exploration and cluster splitting (LSPIO) is proposed in this paper. The lost&exploration mechanism enhances the global search performance of the algorithm, and the cluster splitting mechanism increases the diversity of the population. In this paper, 9 standard test functions are selected for algorithm performance evaluation. Compared with standard pigeon group algorithm and particle swarm algorithm, the results show that the new LSPIO algorithm can effectively avoid premature problems while maintaining good convergence properties