Tag Archives: Robustness

Geometry and beyond: Optimization taxonomy and methods

The power of numerical optimization in engineering design is its ability to rationally and rapidly search through alternatives for the best possible design(s). Parameters in a design that can be varied to search for a “best” design are design variables. Given these, design can be structured as the process of finding the minimum or maximum of some attribute, termed the objective function. For a design to be acceptable, it also must satisfy certain requirements, or design constraints. Optimization is the process of automatically changing the design variables to identify the minimum or maximum of the objective function while satisfying all the required design constraints. [This survey of design optimization methods is in complement to our recent review of design exploration techniques. See also Design exploration vs. design optimization.] Continue reading

Anatomy of design space exploration

Design space exploration is both a class of quantitative methods and a category of software tools for systematically and automatically exploring very large numbers of design alternatives and identifying those with the most optimal performance parameters. The mathematical techniques that underpin design space exploration have been long known—and sometimes applied, in cases where the attendant costs in expertise, time and labor could be justified. What’s changing now is the way fresh software technologies are at last converting these powerful but formerly difficult-to-use methods into practical everyday engineering aids. Continue reading