Reliability-Based Design Optimization Using Akaike Information Criterion for Discrete Information

이산정보의 아카이케 정보척도를 이용한 신뢰성 기반 최적설계

  • Lim, Woo-Chul (Dept. of Automotive Engineering, College of Engineering, Hanyang Univ.) ;
  • Lee, Tae-Hee (Dept. of Automotive Engineering, College of Engineering, Hanyang Univ.)
  • 임우철 (한양대학교 공과대학 자동차공학과) ;
  • 이태희 (한양대학교 공과대학 자동차공학과)
  • Received : 2012.02.27
  • Accepted : 2012.06.09
  • Published : 2012.08.01


Reliability-based design optimization (RBDO) can be used to determine the reliability of a system by means of probabilistic design criteria, i.e., the possibility of failure considering stochastic features of design variables and input parameters. To assure these criteria, various reliability analysis methods have been developed. Most of these methods assume that distribution functions are continuous. However, in real problems, because real data is often discrete in form, it is important to estimate the distributions for discrete information during reliability analysis. In this study, we employ the Akaike information criterion (AIC) method for reliability analysis to determine the best estimated distribution for discrete information and we suggest an RBDO method using AIC. Mathematical and engineering examples are illustrated to verify the proposed method.


Akaike Information Criterion(AIC);Maximum Likelihood Estimation(MLE);Reliability Analysis;Reliability-based Design Optimization;Monte Carlo Simulation;Bogie Frame


Grant : 공간-시간 통계적 모형 기반 최적 설계 기법 연구

Supported by : 한국연구재단


  1. Buslenko, N.P., Golenko, D.I., Shreider, Y.A., Sobol, I.M. and Sragowich, V.G., 1994, The Monte Carlo Method, Pergamon Press.
  2. Cornell, C.A., 1969, "A Probability-based Structural Code," Journal of the American Concrete Institute, Vol.66, No.12, pp.974-985.
  3. Breitung, K., 1984, "Asymptotic Approximations for Multinormal Integrals," Journal of Engineering Mechanics Division, ASCE, Vol. 110, No. 3, pp. 357-366.
  4. Seo, H.S. and Kwak, B.M., 2002, "Efficient Statistical Tolerance Analysis for General Distributions Using Three-Point Information," International Journal of Production Research, Vol. 40, No. 4, pp. 931-944.
  5. Lee, S.H. and Kwak, B.M., 2005, "Reliability-based Design Optimization Using Response Surface Augmented Moment Method," Proceedings of the 6th World Congress on Structural and Multidisciplinary Optimization, Reo de Janeiro, 30 May-3 June, 2005.
  6. Rahman, S. and Xu, H., 2004, "A Univariate Dimension-Reduction Method for Multi-Dimensional Integration in Stochastic Mechanics," Probabilistic Engineering Mechanics, Vol. 19, No. 4, pp. 393-408.
  7. Jung, J.J., 2007, Multiplicative Decomposition Method for Accurate Moment-Based Reliability Analysis, Ph.D. thesis, Hanyang University.
  8. Akaike, H., 1973, "Information theory and an extension of the maximum likelihood principle," Proceedings of the Second International Symposium on Information Theory, pp. 267-281.
  9. Hurvich, C.M., Simonoff, J.S. and Tsai, C.L., 1998, "Smoothing Parameter Selection in Nonparametric Regression using an Improved Akaike Informaion Criterion," Journal of the Royal Statistical Society Series B-Statistical Methodology, Vol.60, pp. 271-293.
  10. Pan, W., 2001, "Akaike's Information Criterion in Generalized Estimating Equations," Biometrics, Vol. 57, pp. 120-125.
  11. Spendelow, J.A., Nichols, J.D., Nisbet, I.C.T., Hays, H., Cormons, G.D., Burger, J., Safina, C., Hines, J.E. and Gochfeld, M., 1995, "Estimating Annual Survival and Movement Rates of Adults within a Metapopulation of Roseate Terns," Ecology, Vol. 76, No. 8, pp. 2415-2428.
  12. Al-Rubaie, K.S., Godefroid L.B. and Lopes J.A.M., 2007, "Statistical Modeling of Fatigue Crack Growth Rate in Inconel Alloy 600," International Journal of Fatigue, Vol. 29, pp. 931-940.
  13. Go, S.J., Lee, M.C. and Park, M.K., 2001, "Fuzzy Sliding Mode Control of a Polishing Robot based on Genetic Algorithm," Journal of Mechanical Science and Technology, Vol. 15, No. 5, pp. 580-591.
  14. Sakamoto, Y., Ishiguro, M. and Kitagawa, G., 1986, Akaike Information Criterion Statistics, KTK Scientific Publishers.

Cited by

  1. Comparative Study of Reliability Analysis Methods for Discrete Bimodal Information vol.37, pp.7, 2013,
  2. Reliability-based Design Optimization for Lower Control Arm using Limited Discrete Information vol.22, pp.2, 2014,
  3. Forecasting Model Design of Fire Occurrences with ARIMA Models vol.19, pp.2, 2015,
  4. The strength analysis and probabilistic design of a bogie frame with incomplete probabilistic information vol.32, pp.3, 2018,