Soft Computing

, Volume 21, Issue 24, pp 7519–7541 | Cite as

Biogeography-based learning particle swarm optimization

  • Xu ChenEmail author
  • Huaglory Tianfield
  • Congli Mei
  • Wenli Du
  • Guohai Liu
Methodologies and Application


This paper explores biogeography-based learning particle swarm optimization (BLPSO). Specifically, based on migration of biogeography-based optimization (BBO), a new biogeography-based learning strategy is proposed for particle swarm optimization (PSO), whereby each particle updates itself by using the combination of its own personal best position and personal best positions of all other particles through the BBO migration. The proposed BLPSO is thoroughly evaluated on 30 benchmark functions from CEC 2014. The results are very promising, as BLPSO outperforms five well-established PSO variants and several other representative evolutionary algorithms.


Particle swarm optimization Biogeography-based learning Exemplar generation Biogeography-based optimization Migration 



This work was partly supported by the Research Talents Startup Foundation of Jiangsu University (Grant No. 15JDG139), the China Postdoctoral Science Foundation (Grant No. 2016M591783), and the Natural Science Foundation of Jiangsu Province (Grant No. BK20160540). The authors would like to especially thank Dr. Wenyin Gong for his helpful comments on work of this paper. The authors would appreciate the scientific efforts of Dr. N. Hansen, Dr. C. Garcia-Martinez, Dr. J. Zhang, and Dr. Y. Jin in making available the source codes of CMAES, GL-25, JADE, and SL-PSO, and Dr. P. N. Suganthan for providing the source codes of CLPSO, DMSPSO, and SaDE.

Compliance with ethical standards

Conflict of interest

The author declares that there is no conflict of interest.

Ethical approval

The work of this article does not involve use of human participants or animals.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Xu Chen
    • 1
    Email author
  • Huaglory Tianfield
    • 2
  • Congli Mei
    • 1
  • Wenli Du
    • 3
  • Guohai Liu
    • 1
  1. 1.School of Electrical and Information EngineeringJiangsu UniversityZhenjiangChina
  2. 2.School of Engineering and Built EnvironmentGlasgow Caledonian UniversityGlasgowUK
  3. 3.Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of EducationEast China University of Science and TechnologyShanghaiChina

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