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.
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