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Sequential Feasible Domain Sampling of Kriging Metamodel by Using Penalty Function

벌칙함수 기반 크리깅메타모델의 순차적 유용영역 실험계획

  • 이태희 (한양대학교 기계공학부) ;
  • 성준엽 (한양대학교 대학원 기계설계학과) ;
  • 정재준 (한양대학교 대학원 기계설계학과)
  • Published : 2006.06.01

Abstract

Metamodel, model of model, has been widely used to improve an efficiency of optimization process in engineering fields. However, global metamodels of constraints in a constrained optimization problem are required good accuracy around neighborhood of optimum point. To satisfy this requirement, more sampling points must be located around the boundary and inside of feasible region. Therefore, a new sampling strategy that is capable of identifying feasible domain should be applied to select sampling points for metamodels of constraints. In this research, we suggeste sequential feasible domain sampling that can locate sampling points likely within feasible domain by using penalty function method. To validate the excellence of feasible domain sampling, we compare the optimum results from the proposed method with those form conventional global space-filling sampling for a variety of optimization problems. The advantages of the feasible domain sampling are discussed further.

Keywords

Approximate Model;Kriging Metamodel;Sequential Sampling;Feasible Domain Sampling

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