A multi-sequential number-theoretic optimization algorithm using clustering methods

  • Xu Qing-song Email author
  • Liang Yi-zeng 
  • Hou Zhen-ting 


A multi-sequential number-theoretic optimization method based on clustering was developed and applied to the optimization of functions with many local extrema. Details of the procedure to generate the clusters and the sequential schedules were given. The algorithm was assessed by comparing its performance with generalized simulated annealing algorithm in a difficult instructive example and a D-optimum experimental design problem. It is shown the presented algorithm to be more effective and reliable based on the two examples.

Key words

retention ratio cluster contraction local search 

CLC number



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Copyright information

© Central South University 2005

Authors and Affiliations

  • Xu Qing-song 
    • 1
    Email author
  • Liang Yi-zeng 
    • 2
  • Hou Zhen-ting 
    • 1
  1. 1.School of Mathematical Science and Computing TechnologyCentral South UniversityChangshaChina
  2. 2.School of Chemistry and Chemical EngineeringCentral South UniversityChangshaChina

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