Course Objectives
- Define and use optimization terminology and concepts, including concepts of analysis space and design space.
- Apply optimization methods to engineering problems, including developing a model, defining an optimization problem, applying optimization methods, exploring the solution and interpreting results.
- Understand and apply unconstrained optimization theory for continuous problems, including the necessary and sufficient conditions and steepest descent, Newton’s method, conjugate gradient and quasi-Newton methods. Understand basic theorems of quasi-Newton methods.
- Understand and apply discrete algorithms, including branch and bound, exhaustive search and simulated annealing.
- Develop and apply Genetic algorithms.
- Understand and apply constrained optimization theory for continuous problems, including the Kuhn-Tucker conditions and generalized reduced gradient and sequential quadratic programming methods.
- Apply optimization techniques to determine a robust design.
- Have some familiarity with optimization software.
