한국CDE학회논문집 (Korean Journal of Computational Design and Engineering)

  • 제21권4호
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  • Pages.443-452
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  • 2016
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  • 2508-4003(pISSN)
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  • 2508-402X(eISSN)
한국CDE학회 (Society for Computational Design and Engineering)
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고비용 블랙박스 함수의 RBF기반 근사 최적화 기법

A Method for RBF-based Approximate Optimization of Expensive Black Box Functions

  • 박상근 (한국교통대학교 기계공학과)
  • Park, Sangkun (Dept. of Mechanical Engineering, Korean Nat'l Univ. of Transportation)
  • 투고 : 2016.05.18
  • 심사 : 2016.06.21
  • 발행 : 2016.12.01
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초록

This paper proposes a method for expensive black box optimization using radial basis functions (RBFs). The proposed algorithm is a computational strategy that uses a RBF model approximating the expensive black box function to predict an optimum. First, a RBF-based approximation technique is introduced and a sampling plan for estimation of the black box function is described. Then the proposed algorithm is explained, which presents the pseudo-codes for implementation and the detailed description of each step performed in the optimization process. In addition, numerical experiments will be given to analyze the performance of the proposed algorithm, by investigating computation accuracy, number of function evaluations, and convergence history. Finally, geometric distance problem as application example will be also presented for showing the algorithm applicability to different engineering problems.

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참고문헌

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