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Searched for: 1 subject found.
16.888[J] Multidisciplinary Design Optimization
(
)
(Same subject as EM.428[J], IDS.338[J])
Prereq: 18.085 or permission of instructor
Units: 3-1-8
Lecture: TR10-11.30 (1-390)
Systems modeling for design and optimization. Selection of design variables, objective functions and constraints. Overview of principles, methods and tools in multidisciplinary design optimization (MDO). Subsystem identification, development and interface design. Design of experiments (DOE). Review of linear (LP) and non-linear (NLP) constrained optimization formulations. Scalar versus vector optimization problems. Karush-Kuhn-Tucker (KKT) conditions of optimality, Lagrange multipliers, adjoints, gradient search methods, sensitivity analysis, geometric programming, simulated annealing, genetic algorithms and particle swarm optimization. Constraint satisfaction problems and isoperformance. Non-dominance and Pareto frontiers. Surrogate models and multifidelity optimization strategies. System design for value. Students execute a term project in small teams related to their area of interest.
O. de Weck
No required or recommended textbooks
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