Journal of Northeastern University ›› 2005, Vol. 26 ›› Issue (9): 828-831.DOI: -

• OriginalPaper • Previous Articles     Next Articles

Uniform design of initial population and operational parameters of genetic algorithm

He, Da-Kuo (1); Wang, Fu-Li (1); Jia, Ming-Xing (1)   

  1. (1) Key Laboratory of Process Industry Automation, Northeastern University, Shenyang 110004, China
  • Received:2013-06-24 Revised:2013-06-24 Online:2005-09-15 Published:2013-06-24
  • Contact: He, D.-K.
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Abstract: Based on the study on how to set the initial population and operational parameters of operators, a conclusion can be drawn that distribution of the initial population and the selection of operational parameters of operators directly concerns global convergence and searching efficiency of genetic algorithm. The reasonable setting of initial population and operational parameters is an important problem in the application of genetic algorithm to performing optimization calculation. At the same time, the initial population of genetic algorithm must reflect the information on solution space scientifically. During the setting of operational parameters attention must be paid to both diversity and fastness to coordinate them well. Based on optimization design theory, a method is proposed to establish initial population and operational parameters simultaneously by uniform design. A simplified calculation method is thus proposed using equivalent principle of uniform design to obtain uniform initial population. Simulation results show that the method is feasible and effective.

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