Abstract

Multidisciplinary design optimization (MDO) has been a field of research for 25 years. It refers to the formulation of the design problem in mathematical models and applying optimization techniques to find the minimum or maximum of a predefined objective function, possibly subject to a set of constraints. MDO has become an important tool in concurrent engineering (CE), with the ability to handle many design variables (DV) across various disciplines. Advances in computer technologies and software engineering have facilitated the practical application of MDO in industry, including aerospace, automotive, shipbuilding, etc. However, active research and development in MDO continues. The creative input of the human designer to the design process is critical and must be integrated in the MDO process. For MDO to be effective in the design of modern complex systems it must also incorporate non-technical disciplines, such as finance, environment, operational support, etc. It remains a challenge to do model them with adequate fidelity. Simulations and analytical models have imbedded assumptions, inaccuracies and approximations. How do we deal with these in an MDO environment? This chapter gives an introduction to MDO with an historical review, a discussion on available numerical optimization methods each with their specific features, the various MDO architectures and decompositions and two case studies where MDO has been applied successfully.

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