We use them because they are particularly well suited for multi-objective optimization. They are also a global techniqe as opposed to gradient based methods an

We use them because they are particularly well suited for multi-objective optimization. They are also a global techniqe as opposed to gradient based methods and have great scaling properties. Important because each evaluation of the objective function takes ten minutes for us. GAs have found a niche in a lot of "obscure" engineering situations. Anything where you need to optimize an expensive black box function is at least worth a try with a GA. I know they are used in analog IC design, civil engineer, and aerospace.