ESD.77J Multidisciplinary System Design Optimization
Engineering 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. Review of linear and non-linear constrained optimization formulations. Scalar versus vector optimization problems from systems engineering and architecting of complex systems. Heuristic search methods: Tabu search, simulated annealing, genetic algorithms. Sensitivity, tradeoff analysis and isoperformance. Multiobjective optimization and pareto optimality. System design for value. Specific applications from aerospace, mechanical, civil engineering and system architecture.
This class has 18.085 as a prerequisite.
This class counts for a total of 12 credits. This is a graduate-level class.
You can find more information on MIT OpenCourseWare at the Multidisciplinary System Design Optimization site.
© Copyright 2015 Yasyf Mohamedali