Study on a Robust Optimization Algorithm Using Latin Hypercube Sampling Experiment and Multiquadric Radial Basis Function

Latin Hypercube Sampling Experiment와 Multiquadric Radial Basis Function을 이용한 최적화 알고리즘에 대한 연구

  • Zhang, Yanli (Dept. of Electrical Eng, Chungbuk National University) ;
  • Yoon, Hee-Sung (Dept. of Electrical Eng, Chungbuk National University) ;
  • Koh, Chang-Seop (Dept. of Electrical Eng, Chungbuk National University)
  • ;
  • 윤희성 (충북대학교 전기공학과) ;
  • 고창섭 (충북대학교 전기공학과)
  • Published : 2007.04.19

Abstract

This paper presents a "window-zoom-out" optimization strategy with relatively fewer sampling data. In this method, an optimal Latin hypercube sampling experiment based on multi-objective Pareto optimization is developed to obtain the sampling data. The response surface method with multiquadric radial basis function combined with (1+$\lambda$) evolution strategy is used to find the global optimal point. The proposed method is verified with numerical experiments.

Keywords