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Development of a Branch-and-Bound Global Optimization Based on B-spline Approximation

비스플라인 분지한계법 기반의 전역최적화 알고리즘 개발

  • Published : 2010.02.01

Abstract

This paper presents a new global optimization algorithm based on the branch-and-bound principle using Bspline approximation techniques. It describes the algorithmic components and details on their implementation. The key components include the subdivision of a design space into mutually disjoint subspaces and the bound calculation of the subspaces, which are all established by a real-valued B-spline volume model. The proposed approach was demonstrated with various test problems to reveal computational performances such as the solution accuracy, number of function evaluations, running time, memory usage, and algorithm convergence. The results showed that the proposed algorithm is complete without using heuristics and has a good possibility for application in large-scale NP-hard optimization.

본 연구는 비스플라인 근사기법을 사용한 분지한계법 기반의 새로운 전역 최적화 알고리즘에 관한 것이다. 본 연구에서는 알고리즘 구성 요소 및 이들의 구현 내용에 관한 상세히 설명한다. 핵심 요소로서, 상호분리되는 부공간으로의 설계 공간의 분할 작업이 있고, 이들 분할 부공간의 한계값 계산 작업이 있는데, 이들 모두는 실수형 비스플라인 볼륨모델에 의해 구현된다. 본 연구 알고리즘은 다양한 테스트 문제들을 가지고 해의 정확성, 함수호출 회수, 알고리즘 수행시간, 메모리 사용량, 알고리즘 수렴성 등 그 계산 성능들을 평가한다. 이러한 평가 결과는 제안 알고리즘이 직관에 의존하지 않는 완전 알고리즘이며, 대용량의 최적화 문제에도 높은 가능성이 있음을 보여주는 것이다.

Keywords

References

  1. Pinter, J.D., 1996, Global Optimization in Action, Kluwer, Dordrecht.
  2. Floudas, C.A., 2000, Deterministic Global Optimization: Theory, Methods and Applications, Kluwer Academic Publishers.
  3. Neumaier, A., 2004, “Complete Search in Continuous Global Optimization and Constraint Satisfaction,” in: Acta Numerica, Cambridge Univ. Press, pp.1-99.
  4. Floudas, C.A., 2007, “Overview of aBB-based Approaches In Deterministic Global Optimization,” Workshop on Global Optimization, Imperial College London, 15-17 Dec.
  5. Al-Khayyal, F.A. and Sherali, H.D., 2000, “On finitely terminating branch-and-bound algorithms for some global optimization problems,” SIAM J. Optimization, Vol.10, pp.1049-1057. https://doi.org/10.1137/S105262349935178X
  6. Audet, C., Hansen, P., Jaumard, B., and Savard, G., 2000, “A Branch and Cut Algorithm for Nonconvex Quadratically Constrained Quadratic Programming,” Math. Programming, Vol.87, pp.131-152. https://doi.org/10.1007/s101079900106
  7. Park, S, 2009, “A Rational B-spline Hypervolume for Multidimensional Multivariate Modeling,” Journal of Mechanical Science and Technology, Vol.23, pp.1967-1981. https://doi.org/10.1007/s12206-009-0513-2
  8. Piegl, L. and Tiller, W., 1995, The NURBS Book, Springer-Verlag.
  9. De Boor, C., 1978, A Practical Guide to Splines, New York, Springer-Verlag.
  10. Stein, M., 1987, “Large Sample Properties of Simulations Using Latin Hypercube Sampling,” Technometrics, Vol.29, pp.143-151. https://doi.org/10.2307/1269769
  11. Huyer, W. and Neumaier, A., 1999, "Global Optimization by Multilevel Coordinate Search," Journal of Global Optimization, Vol. 14, pp.331-355. https://doi.org/10.1023/A:1008382309369
  12. Neumaier, A., 2004, “Complete Search in Continuous Global Optimization and Constraint Satisfaction,” pp.1-99 in: Acta Numerica, Cambridge Univ. Press.