Scalar optimization with linear and NOnlinear Constraints using EVOlution Strategies

  • To Thanh Binh
  • Ulrich Korn
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1226)


This paper introduces a new EVOlution Strategy for scalar optimization with Linear and NOnlinear Constraints (EVOSLINOC) which is robust to obtain a good approximation of a feasible global minimum. EVOSLINOC is based on the new concept of C and F-fitness allowing systematically to handle constraints and (in)feasible individuals. In addition a number of ideas for using (in)feasible niche individuals which enable to explore new feasible areas and to make the population quickly to evolve towards a feasible global minimum is proposed. The performance of the EVOSLINOC can be successfully evaluated on many benchmark optimization problems [11, 10].


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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • To Thanh Binh
    • 1
  • Ulrich Korn
    • 1
  1. 1.Institute of AutomationUniversity of MagdeburgGermany

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