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If you are interested in our recent article Self-adjusting parameter control for surrogate-assisted constrained optimization under limited budgets  which appeared in the journal Applied Soft Computing (ASOC), please take the opportunity to follow this link: For a period until November, 02, 2017, this link will provide the free download of the final journal article. (After this period, the link is still

valid, but the usual ScienceDirect access rules will apply. So take the opportunity! smiley)

We are happy that our article got finally accepted, after very constructive rounds of discussion with the reviewers. Thanks!


The highlights of the arcticle in short:

  • Solves 10 of 11 G-problems (constrained optimization) in less than 500 function evaluations.
  • Self-adjusting algorithm requires no parameter tuning.
  • RBF-based surrogate modeling for constraints and objective function.
  • Better understanding of RBF modeling: how to avoid common modeling problems.