Abstract
All previous chapters considered solutions of design optimisation ‘at fixed design’ conditions. However as discussed in Chap. 4, there are many situations in engineering where a design does not operate at ‘fixed design’ points due to uncertainties in values of manufacturing or operational parameters. In this chapter we illustrate the use of advanced EAs for five (5) robust design optimisation problems taking into account uncertainties.
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References
Drela M. A user’s guide to MSES V 2.3. MIT
Lee DS, Periaux J, Gonzalez LF, Srinivas K, Onate E (2012) Robust multidisciplinary UAS design optimisation. Struct Multidiscip Optim 45(3):433–450
Hague D (January 1978) General aviation synthesis program (GASP), NASA
Jameson, Caughey D, Newman P, Davis R A brief description of the Jameson Caughey NYU Transonic Swept-Wing Computer Program FLO22, NASA Technical Memorandum, NASA TM X–73996
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Periaux, J., Gonzalez, F., Lee, D. (2015). Robust Multi-Objective and Multi-Disciplinary Model Optimization Test Cases. In: Evolutionary Optimization and Game Strategies for Advanced Multi-Disciplinary Design. Intelligent Systems, Control and Automation: Science and Engineering, vol 75. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-9520-3_9
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DOI: https://doi.org/10.1007/978-94-017-9520-3_9
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