I am working in a project to assist an experimental team in optimizing reaction conditions. The problem involves a large number of dimensions, i.e. 30+ reactants which we are trying out different concentrations to achieve the highest yield of a certain product.
I am familiar with stochastic optimization methods such as simulated annealing, genetic algorithms, which seemed like a good approach to this problem. The experimental team proposes using design of experiments (DoE), which I'm not too familiar with.
So my question is, what are the advantages/disadvantages of DoE (namely fractional factorial and response surface method I believe) versus stochastic optimization methods, and are there use cases where one is preferred over the other?