A Simple Brain Storm Optimization Algorithm via Visualizing Confidence Intervals

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10593)

Abstract

Visualizing confidence intervals method developed recently for benchmarking stochastic optimization algorithm is adopted in this paper to benchmark and study the brain storm optimization algorithm in depth. Through analyzing numerical effects of different components of brain storm optimization, a simplified brain storm optimization algorithm is developed. It is tested and shown to perform better than the original brain storm optimization algorithm in the objective space.

Keywords

Brain storm optimization Visualizing confidence intervals Benchmarking Swarm intelligence Evolutionary computation 

Notes

Acknowledgement

This work was supported in part by the National Natural Science Foundation of China (No. 11271069), in part by Natural Science Foundation of Guangdong Province, China (No. 2015A030313648), in part by Natural Science Basic Research Plan in Shaanxi Province, China (No. 2017JQ6070), and in part by the Fundamental Research Funds for the Central University (Nos. GK201703062, GK201603014).

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.School of Computer Science and Network SecurityDongguan University of TechnologyDongguanChina
  2. 2.School of Computer ScienceShaanxi Normal UniversityXi’anChina
  3. 3.Key Laboratory of Modern Teaching TechnologyMinistry of EducationXi’anChina
  4. 4.School of Physics and Information TechnologyShaanxi Normal UniversityXi’anChina
  5. 5.Department of Computer Science and EngineeringSouthern University of Science and TechnologyShenzhenChina

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