Optimization is typically achieved through a combination of experimental and computational methods:
Experimental: Systematic variation of experimental conditions and analysis of outcomes to find the optimal configuration. Computational: Using computer simulations and machine learning to predict optimal conditions before conducting physical experiments. Iterative Process: Often, optimization involves multiple cycles of testing and refinement.
