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Benchmarking multidisciplinary design optimization algorithms

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Abstract

A comparison of algorithms for multidisciplinary design optimization (MDO) is performed with the aid of a new software framework. This framework, pyMDO, was developed in Python and is shown to be an excellent platform for comparing the performance of the various MDO methods. pyMDO eliminates the need for reformulation when solving a given problem using different MDO methods: once a problem has been described, it can automatically be cast into any method. In addition, the modular design of pyMDO allows rapid development and benchmarking of new methods. Results generated from this study provide a strong foundation for identifying the performance trends of various methods with several types of problems.

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References

  • Alexandrov NM, Kodiyalam S (1998) Initial results of an MDO evaluation survey. AIAA Paper 98-4884

  • Alexandrov NM, Lewis RM (1999) Comparative properties of collaborative optimization and other approaches to MDO. In: Proceedings of the first ASMO UK/ISSMO conference on engineering design optimization

  • Alexandrov NM, Lewis RM (2002) Analytical and computational aspects of collaborative optimization for multidisciplinary design. AIAA J 40(2):301–309

    Article  Google Scholar 

  • Braun RD, Kroo IM (1997) Development and application of the collaborative optimization architecture in a multidisciplinary design environment. In: Alexandrov N, Hussaini MY (eds) Multidisciplinary design optimization: state of the art. SIAM, Philadelphia, pp 98–116

    Google Scholar 

  • Braun RD, Kroo IM, Gage PJ (1993) Post-optimality analysis in aerospace vehicle design. In: Proceedings of the AIAA aircraft design, systems and operations meeting, Monterey, CA, AIAA 93-3932

  • Braun RD, Gage PJ, Kroo IM, Sobieski IP (1996) Implementation and performance issues in collaborative optimization. AIAA Paper 96-4017

  • Brown NF, Olds JR (2006) Evaluation of multidisciplinary optimization techniques applied to a reusable launch vehicle. J Spacecr Rockets 43(6):1289–1300

    Article  Google Scholar 

  • Cramer EJ, Dennis JE, Frank PD, Lewis RM, Shubin GR (1994) Problem formulation for multidisciplinary optimization. SIAM J Optim 4(4):754–776

    Article  MATH  MathSciNet  Google Scholar 

  • DeMiguel A-V, Murray W (2000) An analysis of collaborative optimization methods. In: Proceedings of the 8th AIAA/USAF/NASA/ISSMO symposium on multidisciplinary analysis and optimization, Long Beach, CA, AIAA 2000-4720

  • DeMiguel V, Murray W (2006) A local convergence analysis of bilevel decomposition algorithms. Optim Eng 7(2):99–133

    Article  MATH  MathSciNet  Google Scholar 

  • Gill PE, Murray W, Saunders MA (2002) SNOPT: an SQP algorithm for large-scale constrained optimization. SIAM J Optim 12(4):979–1006

    Article  MATH  MathSciNet  Google Scholar 

  • Kodiyalam S (1998) Evaluation of methods for multidisciplinary design optimization (MDO), Part 1. NASA Report CR-2000-210313

  • Langtangen HP (2004) Python scripting for computational science. Springer, Berlin

    MATH  Google Scholar 

  • Martins JRRA, Sturdza P, Alonso JJ (2003) The complex-step derivative approximation. ACM Trans Math Softw 29(3):245–262

    Article  MATH  MathSciNet  Google Scholar 

  • Martins JRRA, Alonso JJ, Reuther JJ (2005) A coupled-adjoint sensitivity analysis method for high-fidelity aero-structural design. Optim Eng 6(1):33–62

    Article  MATH  Google Scholar 

  • Martins JRRA, Marriage C, Tedford NP (2008) pyMDO: an object-oriented framework for multidisciplinary design optimization. ACM Trans Math Softw 36(4):1–23

    Article  Google Scholar 

  • Padula SL, Alexandrov N, Green LL (1996) MDO test suite at NASA Langley research center. In: Proceedings of the 6th AIAA/NASA/ISSMO symposium on multidisciplinary analysis and optimization, Bellevue, WA, AIAA 1996-4028

  • Perez RE, Liu HHT, Behdinan K (2004) Evaluation of multidisciplinary optimization approaches for aircraft conceptual design. In: Proceedings of the 10th AIAA/ISSMO multidisciplinary analysis and optimization conference, Albany, NY, AIAA 2004-4537

  • Sellar RS, Batill SM, Renaud JE (1996) Response surface based, concurrent subspace optimization for multidisciplinary system design. In: Proceedings of the 34th AIAA aerospace sciences meeting and exhibit, Reno, NV, AIAA 1996-0714

  • Sobieski IP, Kroo IM (2000) Collaborative optimization using response surface estimation. AIAA J 38(10):1931–1938

    Article  Google Scholar 

  • Sobieszczanski-Sobieski J (1988) Optimization by decomposition: a step from hierarchic to non-hierarchic systems. NASA Technical Report CP-3031

  • Sobieszczanski-Sobieski J, Altus TD, Phillips M, Sandusky R (2003) Bilevel integrated system synthesis for concurrent and distributed processing. AIAA J 41(10):1996–2003

    Article  Google Scholar 

  • Wujek B, Renaud J, Batill S (1997) A concurrent engineering approach for multidisciplinary design in a distributed computing environment. In: Alexandrov N, Hussaini MY (eds) Multidisciplinary design optimization: state of the art. SIAM, Philadelphia, pp 189–208

    Google Scholar 

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Authors and Affiliations

  1. University of Toronto Institute for Aerospace Studies, Toronto, ON, M3H 5T6, Canada

    Nathan P. Tedford & Joaquim R. R. A. Martins

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  1. Nathan P. Tedford
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  2. Joaquim R. R. A. Martins
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Correspondence to Joaquim R. R. A. Martins.

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Tedford, N.P., Martins, J.R.R.A. Benchmarking multidisciplinary design optimization algorithms. Optim Eng 11, 159–183 (2010). https://doi.org/10.1007/s11081-009-9082-6

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  • DOI: https://doi.org/10.1007/s11081-009-9082-6

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