대한기계학회논문집A (Transactions of the Korean Society of Mechanical Engineers A)

  • 제38권5호
  • /
  • Pages.489-495
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  • 2014
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  • 1226-4873(pISSN)
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  • 2288-5226(eISSN)
대한기계학회 (The Korean Society of Mechanical Engineers)
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순차적 실험계획법과 마이크로 유전알고리즘을 이용한 최적화 알고리즘 개발

Development of Optimization Algorithm Using Sequential Design of Experiments and Micro-Genetic Algorithm

  • 이정환 (오산대학교 자동차공학과) ;
  • 서명원 (성균관대학교 기계공학부)
  • 투고 : 2013.07.16
  • 심사 : 2014.01.10
  • 발행 : 2014.05.01
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초록

마이크로 유전알고리즘은 적은 수의 개체 사용 및 무작위 개체 구성을 통한 돌연변이 기능 대체의 특징을 갖는 진화연산을 수행하여 일반적인 유전알고리즘이 갖는 각 세대당 많은 계산 량이 요구되는 단점을 극복하고자 하였다. 이러한 마이크로 알고리즘은 특히 설계변수가 3~5 개를 갖는 문제에 효율적이라는 것이 많은 연구자들에 의하여 알려졌다. 따라서 본 연구의 목적은 순차적 실험계획법과 마이크로 유전알고리즘을 이용한 최적화 알고리즘을 개발하는 것이며, 이를 수학예제와 구조물 문제에 적용하여 실용성을 확인하고자 한다. 순차적 실험계획법은 저자들의 선행연구에서 제안되었으며, 실험계획법과 반응표면법을 이용하는 근사최적화 기법에 의한 시행착오적인 반복과정을 최소화하고자 하는 방법으로써, 행렬실험과 평균분석을 반복 적용하는 개념이다.

A micro-genetic algorithm (MGA) is one of the improved forms of a genetic algorithm. It is used to reduce the number of iterations and the computing resources required by using small populations. The efficiency of MGAs has been proved through many problems, especially problems with 3-5 design variables. This study proposes an optimization algorithm based on the sequential design of experiments (SDOE) and an MGA. In a previous study, the authors used the SDOE technique to reduce trial-and-error in the conventional approximate optimization method by using the statistical design of experiments (DOE) and response surface method (RSM) systematically. The proposed algorithm has been applied to various mathematical examples and a structural problem.

키워드

참고문헌

  1. Kim, C. W. and Park, T. W., 1994, "Optimal Design of Mechanisms Using a Least Experimental Plan Method," Trans. Soc. Mech. Eng. A, Vol. 18, No. 11, pp.2883-2893.
  2. Kim, S. J, Park, C. J. and Park, T. W., 1996, "Suspension Parameter Design Using a Design of Experiments," Trans. of the KSAE, Vol. 4, No. 1, pp.16-27.
  3. Lee, J. H. and Suh, M. W., 2008, "Development of Optimization Algorithm for Unconstrained Problems Using the Sequential Design of Experiments and Artificial Neural Network," Trans. Soc. Mech. Eng. A, Vol. 32, No. 3, pp.258-266. https://doi.org/10.3795/KSME-A.2008.32.3.258
  4. Lee, J. S., Kim, J. H., Lee, H. J. and Koo, B. H., 2002, "Applications of Micro Genetic Algorithms to Engineering Design Optimization," Spring Conference Proceedings of the KSME, pp.528-533.
  5. Goldberg, D. E., 1989, "Sizing Populations for Serial and Parallel Genetic Algorithms," Proceedings 3rd International Conference on Genetic Algorithms and Their Applications, Arlington, VA, pp.70-79.
  6. Krishnakumar, K., 1989, "Micro-Genetic Algorithm for Stationary and Non-Stationary Function Optimization," Intelligent Control and Adaptive Systems, Vol. 11, No. 96, pp.282-296.
  7. Baek, S. H., Lee, D. W., Lee, K. Y., Cho, S. S. and Joo, W. S., 2002, "Application of Sequential Quadratic Programming on Multi-Objective Optimization Using the Stochastic Method," Spring conference Proceedings of the KSME, pp.954-961.
  8. Arora, J. S., 1989, Introduction to Optimum Design, McGraw-Hill, New York.
  9. Reklaitis, G. V., Ravindran, A. and Ragsdell, K. M., 1983, Engineering Optimization Methods and Applications, John Wiley & Sons, Inc., New York, pp. 123-124.
  10. Hock, W. and Schittkowski, K., 1981, "Lecture Notes in Economics and Mathematical Systems," Springer-Verlag, New York.
  11. Rao, S. S., 1996, Engineering Optimization 3rd Edition, Wiley Interscience.
  12. Kim, H. J., Kim, B. Y. and Suh, M. W., 2011, "Development of a Topology Optimization Program Considering Density and Homogenization Methods," International Journal of Precision Engineering and Manufacturing, Vol. 12, No. 2, pp.303-312. https://doi.org/10.1007/s12541-011-0040-9
  13. Kim, B. Y., Son, Y. T., Jeong, C. M., Kim, S. W. and Suh, M. W., 2008, "A Study to Maximize the Crash Energy Absorption Efficiency Within the Limits of Crash Space," Journal of Mechanical Science and Technology, Vol. 22, No. 1, 1537-1543. https://doi.org/10.1007/s12206-008-0430-9