Abstract
We propose solution methods for multidisciplinary design optimization (MDO) under uncertainty. This is a class of stochastic optimization problems that engineers are often faced with in a realistic design process of complex systems. Our approach integrates solution methods for reliability-based design optimization (RBDO) with solution methods for deterministic MDO problems. The integration is enabled by the use of a deterministic equivalent formulation and the first order Taylor’s approximation in these RBDO methods. We discuss three specific combinations: the RBDO methods with the multidisciplinary feasibility method, the all-at-once method, and the individual disciplinary feasibility method. Numerical examples are provided to demonstrate the procedure.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Alexandrov NM, Kodiyalam S (1998) Initial results of an MDO method evaluation study. In: 7th AIAA/USAF/NASA/ISSMO symposium on multidisciplinary analysis and optimization, St. Louis. AIAA 98-4884 Paper
Batill SM, Renaud JE, Gu X (2000) Modeling and simulation uncertainty in multidisciplinary design optimization. In: 9th AIAA/USAF/NASA/ISSMO symposium on multidisciplinary analysis and optimization. AIAA 2000-4803 Paper
Braun RD, Kroo IM (1996) Development and applications of the collaborative optimization architecture in a multidisciplinary design environment. In: Alexandrov N, Hussaini MY (eds) Multidisciplinary design optimization: state-of-the-art
Braun RD, Powell RW, Lepsch RA, Stanley DO, Kroo IM (1995) Comparison of two multidisciplinary optimization strategies for launch-vehicle design. J Spacecr Rockets 32(3):404–410
Chen X, Hasselman TK, Neill DJ (1997) Reliability based structural design optimization for practical applications. In: 38th AIAA/ASME/ASCE/AHS/ASC structures, structural dynamics and materials conference. AIAA-97-1403
Chiralaksanakul A, Mahadevan S (2005) First order approximation methods in reliability-based design optimization. J Mech Des 127(5):851–857
Cramer EJ, Dennis JE Jr, Frank PD, Lewis RM, Shubin GR (1994) Problem formulation for multidisciplinary optimization. SIAM J Optim 4:754–776
Du X, Chen W (2003) Collaborative reliability analysis for multidisciplinary systems design. In: 9th AIAA/NASA/USAF/ISSMO symposium on multidisciplinary analysis and optimization, Atlanta. AIAA-2002-5474
Du X, Chen W (2004) Sequential optimization and reliability assessment method for efficient probabilistic design. J Mech Des 126(2):225–233
Du X, Sudjianto A (2004) First-order saddlepoint approximation for reliability analysis. AIAA J 42(6):1199–1207
Du X, Sudjianto A, Chen W (2004) An integrated framework for optimization under uncertainty using inverse reliability strategy. J Mech Des 126(4):562–570
Haftka RT (1985) Simultaneous analysis and design. AIAA J 23:1099–1103
Hulme KF, Bloebaum CL (2000) A simulation-based comparison of multidisciplinary design optimization solution strategies using CASCADE. Struct Multidiscip Optim 19:17–35
Koch PN, Wujek B, Golovidov O, Simpson TW (2002) Facilitating probabilistic multidisciplinary design optimization using Kriging approximation models. In: 9th AIAA/ISSMO symposium on multidisciplinary analysis and optimization, Atlanta. AIAA 2002-5415 Paper
Liang J, Mourelatos Z, Tu J (2004) A single-loop method for reliability-based design optimization. In: Proceedings of the ASME design engineering technical conferences, Salt Lake
Mahadevan S, Gantt CW (2000) Probabilistic design optimization of a multidisciplinary system. In: 9th AIAA/USAF/NASA/ISSMO symposium on multidisciplinary analysis and optimization. AIAA 2000-4807 Paper
Oakley DR, Sues RH, Rhodes GS (1998) Performance optimization of multidisciplinary mechanical systems subject to uncertainties. Probab Eng Mech 13(1):15–26
Padula SL, Alexandrov NM, Green LL (1996) MDO test suite at NASA Langley Research Center. In: 6th AIAA/NASA/ISSMO symposium on multidisciplinary analysis and optimization, Bellvue. AIAA 96-4028 Paper
Smith N (2004) Probabilistic design of multidisciplinary systems. PhD thesis, Vanderbilt University (in progress)
Smith N, Mahadevan S (2005) Probabilistic design of aerospace vehicles: coupling global and local requirements. J Spacecr Rockets 42(4):752–760
Sobieszczanski-Sobieski J, Kodiyalam S (2001) BLISS/S: A new method for two-level structural optimization. Struct Multidiscip Optim 21
Sobieszczanski-Sobieski J, Agte JS, Sandusky RR Jr (1998) Bi-level integrated system synthesis (BLISS). In: 7th AIAA/USAF/NASA/ISSMO symposium on multidisciplinary analysis and optimization, St. Louis. AIAA 98-4916 Paper
Tu J, Choi KK, Park YH (1999) A new study on reliability-based design optimization. J Mech Des 121:557–564
Youn BD, Choi KK (2004) Performance moment integration approach for reliability-based robust design optimization. In: Proceedings of the ASME design engineering technical conferences, Salt Lake
Youn BD, Choi KK, Du L (2004) Enriched performance measure approach (PMA+) for reliability-based design optimization. In: Proceedings of 10th AIAA/ISSMO multidisciplinary analysis and optimization conference. AIAA-2004-4401
Author information
Authors and Affiliations
Corresponding author
Additional information
Anukal Chiralaksanakul is currently a full-time lecturer in the Graduate School of Business Administration at National Institute of Development Administration (NIDA), Bangkok, Thailand.
Rights and permissions
About this article
Cite this article
Chiralaksanakul, A., Mahadevan, S. Decoupled approach to multidisciplinary design optimization under uncertainty. Optim Eng 8, 21–42 (2007). https://doi.org/10.1007/s11081-007-9014-2
Received:
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11081-007-9014-2