From simulation to optimization—Part 2: A perspective on single-objective optimization strategies

As engineering systems become increasingly complex, traditional methods of design exploration and performance tuning, such as trial-and-error and exhaustive simulation, prove inadequate. This paper outlines the journey from manual experimentation to advanced, data-driven optimization, with a focus on single-objective optimization strategies. It discusses the necessity of transitioning to intelligent optimization frameworks, explores various sampling and optimization methods, and introduces the SHERPA algorithm.

Shivani Joshi, Siemens EDA