Usually is perhaps a strong word, but it spans from/over using the expertise of the designer, time-to-market, brute-force monte-carlo, genetic algorithms, optimization tools, etc.
With that said, there are also plenty of papers out there of various detail. But use search words as operational amplifier genetic and neural networks and cadence own optimizer descriptions.
So, there have been many trials throughout the years and success rate has been somewhat limited as the holy graal more often is some other vague cost measure, like for example design time, deadline, "good-enough" mentality, etc.
To be honest, I tend to prefer brute force monte-carlo if I have the luxury of "free" licenses. Associate W, L, I with each transistor. Pick a random value from certain limits. Set up the simulation criteria (dc + tran + ac or so), evaluate and store the results. Then plot those meeting some kind of realistic specification in your x-dimensional graph. Not very academic nor very efficient, but satisfying and no extra brains required. An eight-transistor, two-stage operational amplifier with an RC miller compensation does not give you too many variables to juggle with, in the end.