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Evolian: Evolutionary optimization based on lagrangian with constraint scaling

  • Hyun Myung
  • Jong-Hwan Kim
Issues in Evolutionary Optimization
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1213)

Abstract

In this paper, an evolutionary optimization method, Evolian, is proposed for the general constrained optimization problem, which incorporates the concept of (1) a multi-phase optimization process and (2) constraint scaling techniques to resolve problem of ill-conditioning. In each phase of Evolian, the typical evolutionary programming (EP) is performed using an augmented Lagrangian objective function with a penalty parameter fixed. If there is no improvement in the best objective function in one phase, another phase of Evolian is performed after scaling the constraints and then updating the Lagrange multipliers and penalty parameter. This procedure is repeated until a satisfactory solution is obtained. Computer simulation results indicate that Evolian gives outperforming or at least reasonable results for multivariable heavily constrained function optimization as compared to other evolutionary computation-based methods.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Hyun Myung
    • 1
  • Jong-Hwan Kim
    • 1
  1. 1.Dept. of EEKAISTTaejonKorea

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