Non-Gradient Based Parameter Sensitivity Estimation for Single Objective Robust Design Optimization

[+] Author and Article Information
S. Gunawan, S. Azarm

Department of Mechanical Engineering, University of Maryland College Park, Maryland 20742

J. Mech. Des 126(3), 395-402 (Oct 01, 2003) (8 pages) doi:10.1115/1.1711821 History: Received April 01, 2003; Revised October 01, 2003
Copyright © 2004 by ASME
Topics: Design , Optimization
Your Session has timed out. Please sign back in to continue.


Fiacco, A. V., 1983, Introduction to Sensitivity and Stability Analysis in Nonlinear Programming, Vol. 165 in Mathematics in Science and Engineering, Academic Press, New York.
Taguchi,  G., 1978, “Performance Analysis Design,” Int. J. Prod. Res., 16, pp. 521–530.
Balling,  R. J., Free,  J. C., and Parkinson,  A. R., 1986, “Consideration of Worst-Case Manufacturing Tolerances in Design Optimization,” ASME J. Mech. Des., 108, pp. 438–441.
Sundaresan,  S., Ishii,  K., and Houser,  D., 1992, “Design Optimization for Robustness Using Performance Simulation Programs,” Eng. Optimiz., 20, pp. 163–178.
Parkinson,  A., Sorensen,  C., and Pourhassan,  N., 1993, “A General Approach to Robust Optimal Design,” ASME J. Mech. Des., 115, pp. 74–80.
Zhu,  J., and Ting,  K. L., 2001, “Performance Distribution Analysis and Robust Design,” ASME J. Mech. Des., 123, pp. 11–17.
Hughes, E. J., 2001, “Evolutionary Multi-objective Ranking with Uncertainty and Noise,” Lecture Notes in Computer Science, E. Zitzler, eds., pp. 329–343.
Yu,  J. C., and Ishii,  K., 1998, “Design for Robustness Based on Manufacturing Variation Patterns,” ASME J. Mech. Des., 120, pp. 196–202.
Hirokawa, N., and Fujita, K., 2002, “Mini-Max Type Formulation of Strict Robust Design Optimization under Correlative Variation,” paper no. DAC-34041, Proc. of Design Engineering Technical Conf., Montreal, Canada, Sept 29-Oct 2.
Tsutsui,  S., and Ghosh,  A., 1997, “Genetic Algorithms with a Robust Solution Searching Scheme,” IEEE Trans. on Evolutionary Computation, 1(3), pp. 201–208.
Branke, J., 2001, “Reducing the Sampling Variance when Searching for Robust Solutions,” Proc. of the Genetic and Evolutionary Computation Conference, San Francisco, CA, pp. 235–242.
Du,  X., and Chen,  W., 2000, “Towards a Better Understanding of Modeling Feasibility Robustness in Engineering Design,” ASME J. Mech. Des., 122, pp. 385–394.
Lee, K., and Lee, T. H., 2001, “Fuzzy Multi-Objective Optimization of an Automotive Seat Using Response Surface Model and Reliability Method,” Proc. of the 4th World Congress of Structural and Multidisciplinary Optimization, Dailan, China, June 4–8.
Jin, R., Du, X., and Chen, W., 2001, “The Use of Metamodeling Techniques for Optimization Under Uncertainty,” Paper No. DAC-21039, Proc. of Design Engineering Technical Conf., Pittsburgh, PA, Sept 9–12.
Choi, K. K., and Youn, B. D., 2002, “On Probabilistic Approaches for Reliability-Based Design Optimization,” CD-ROM Proceedings of 9th AIAA/NASA/USAF/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Atlanta, GA, Sept 4–6.
Badhrinath,  K., and Rao,  J. R., 1994, “Bi-Level Models for Optimum Designs which are Insensitive to Perturbations in Variables and Parameters,” Advances in Design Automation, 69(2), pp. 15–23.
Belegundu,  A. D., and Zhang,  S., 1992, “Robustness of Design Through Minimum Sensitivity,” ASME J. Mech. Des., 114, pp. 213–217.
Goldberg, D. E., 1989, Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley, Reading, MA.
Van Veldhuizen, D. A., and Lamont, G. B., 1998, “Multiobjective Evolutionary Algorithm Research: A History and Analysis,” Technical Report TR-98-03, Air Force Institute of Technology, Wright-Patterson AFB, OH.
Ragsdell,  K. M., and Phillips,  D. T., 1976, “Optimal Design of a Class of Welded Structures Using Geometric Programming,” ASME J. Ind., 98(3), pp. 1021–1025, Series B.
Reklaitis, G. V., Ravindran, A., and Ragsdell, K. M., 1983, Engineering Optimization Methods and Applications, A Wiley-Interscience Publication, NY.


Grahic Jump Location
Sensitivity region of a design alternative
Grahic Jump Location
Concept of directional sensitivity
Grahic Jump Location
Most and least sensitive directions of a sensitivity region
Grahic Jump Location
Worst case estimation of the sensitivity region
Grahic Jump Location
Interior and exterior circles of a normalized tolerance region
Grahic Jump Location
Tolerance region and robustness index
Grahic Jump Location
Bi-level solution approach to robust optimization
Grahic Jump Location
Surface plot of the wine-bottle function
Grahic Jump Location
Distributions of robust optima on a contour plot
Grahic Jump Location
Distributions of robust optima on a cross-section plot
Grahic Jump Location
Sensitivity region and WCSR of the optima: (a) conventional, (b) robust
Grahic Jump Location
Sensitivity comparison between conventional and robust optima




Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In