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Design Optimization Educational Series: Optimization Analysis— How do I configure and run an optimization study to find better designs?

Format: On-Demand Webcast (Pdf Presentation)
Facilitator(s): Grant Soremekun, Phoenix Integration

Phoenix Integration presented the second in a three part educational series on the application of Design Optimization to real world problems

  1. Sensitivity Analysis: Determining key drivers in a design.
  2. Optimization Analysis: Automated search techniques to find optimal solutions
  3. Probabilistic Analysis: Exploring the robustness of a solution.

Successful application of Design Optimization requires progressive exploration of a problem starting with Sensitivity Analysis. Once key design parameters have been identified and a basic understanding of the search space is understood, optimization algorithms can be employed to help find better designs.

The focus of this webcast was on Optimization Algorithms. Presentation topics included:

  • How to set up an optimization problem: objectives, design variables, and constraints.
  • How to choose the right algorithm. Specific algorithms that will be discussed include Gradient, Genetic, and Response Surface-based algorithms.
  • Visualizing, interpreting, and communicating optimization results.
  • Multi-objective optimization (e.g., Cost As an Independent Variable (CAIV) analysis).

Optimization is a tricky subject, but can yield significant benefits when applied properly. This presentation provided an introduction to optimization and demonstrated how to run a multi-objective study using tools available in the Phoenix 2006 Product Suite.

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