The Effect of Initial Population Sampling on the Convergence of Multi-Objective Genetic Algorithms

  • Silvia Poles
  • Yan Fu
  • Enrico Rigoni
Conference paper
Part of the Lecture Notes in Economics and Mathematical Systems book series (LNE, volume 618)


This paper aims to demonstrate that the initial population plays an important role in the convergence of genetic algorithms independently from the algorithm and the problem. Using a well-distributed sampling increases the robustness and avoids premature convergence. The observation is proved using MOGA-II and NSGA-II with different sampling methods. This result is particularly important whenever the optimization involves time-consuming functions.


Convergence Initial population MOGA-II, Multi-objective genetic algorithms NSGA-II 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Silvia Poles
    • 1
  • Yan Fu
    • 2
  • Enrico Rigoni
    • 1
  1. 1.ESTECO, Area Science Park—PadricianoItaly
  2. 2.Ford Motor Company MD 2115DearbornUSA

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