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Open Access Publications from the University of California

Fortify particle swam optimizer (PSO) with principal components analysis: A case study in improving bound-handling for optimizing high-dimensional and complex problems

  • Author(s): Chu, W
  • Gao, X
  • Sorooshian, S
  • et al.

It is reported that the absorbing bound-handling approach may paralyze PSO when it is applied to high-dimensional and complex problems. In this study, we introduce principal components analysis (PCA) into PSO in order to remedy the problem caused by the absorbing bound-handling approach. The experiments on 100-D composition functions demonstrate the effectiveness of PCA. Furthermore, the strong influence of bound-handling on PSO is also evidently revealed by the results. The fact that none of the studied bound-handling methods excels on all of the benchmark functions highlights the necessity of developing more sophisticated and robust bound-handling approaches that can facilitate the application of PSO on high-dimensional problems. © 2011 IEEE.

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