# Multidisciplinary design optimization

Multi-disciplinary design optimization (MDO) is a field of engineering that uses optimization methods to solve design problems incorporating a number of disciplines. It is also known as multidisciplinary optimization and multidisciplinary system design optimization (MSDO).

MDO allows designers to incorporate all relevant disciplines simultaneously. The optimum of the simultaneous problem is superior to the design found by optimizing each discipline sequentially, since it can exploit the interactions between the disciplines. However, including all disciplines simultaneously significantly increases the complexity of the problem.

These techniques have been used in a number of fields, including automobile design, naval architecture, electronics, architecture, computers, and electricity distribution. However, the largest number of applications have been in the field of aerospace engineering, such as aircraft and spacecraft design. For example, the proposed Boeing blended wing body (BWB) aircraft concept has used MDO extensively in the conceptual and preliminary design stages. The disciplines considered in the BWB design are aerodynamics, structural analysis, propulsion, control theory, and economics.

Traditionally engineering has normally been performed by teams, each with expertise in a specific discipline, such as aerodynamics or structures. Each team would use its members' experience and judgement to develop a workable design, usually sequentially. For example, the aerodynamics experts would outline the shape of the body, and the structural experts would be expected to fit their design within the shape specified. The goals of the teams were generally performance-related, such as maximum speed, minimum drag, or minimum structural weight.

find ${\displaystyle \mathbf {x} }$ that minimizes ${\displaystyle J(\mathbf {x} )}$ subject to ${\displaystyle \mathbf {g} (\mathbf {x} )\leq \mathbf {0} }$, ${\displaystyle \mathbf {h} (\mathbf {x} )=\mathbf {0} }$ and ${\displaystyle \mathbf {x} _{lb}\leq \mathbf {x} \leq \mathbf {x} _{ub}}$
• Avriel, M., Rijckaert, M.J. and Wilde, D.J. (eds.), Optimization and Design, Prentice-Hall, 1973.
• Avriel, M. and Dembo, R.S. (eds.), Mathematical Programming Studies on Engineering Optimization, North-Holland, 1979.
• Cramer, E.J., Dennis Jr., J.E., Frank, P.D., Lewis, R.M., and Shubin, G.R., Problem Formulation for Multidisciplinary Optimization, SIAM J. Optim., 4 (4): 754-776, 1994.
• Deb, K. "Current trends in evolutionary multi-objective optimization", Int. J. Simul. Multi. Design Optim., 1 1 (2007) 1-8.
• Martins, J. R. R. A. and Lambe, A. B., "Multidisciplinary design optimization: A Survey of architectures", AIAA Journal, 51(9), 2013. DOI: 10.2514/1.J051895
• Siddall, J.N., Optimal Engineering Design, CRC, 1982.
• Vanderplaats, G. N., Multidiscipline Design Optimization, Vanderplaatz R&D, Inc., 2007.
• Viana, F.A.C., Simpson, T.W., Balabanov, V. and Toropov, V. "Metamodeling in multidisciplinary design optimization: How far have we really come?" AIAA Journal 52 (4) 670-690, 2014 (DOI: 10.2514/1.J052375)
...
Wikipedia