I would like to know whether stochastic optimization and robust optimization are the same and if not, what is the main difference between them. I did an Internet search and I found the following conversation: https://www.quora.com/What-are-the-main-differences-between-stochastic-optimization-and-robust-optimization Here some say it is in fact the same and others say it is not.
My guess would be that in stochastic optimization the distribution of input parameters are known or can be estimated while in robust optimization this is generally not the case. At least you do not use random variables with certain distributions when defining the optimization problem. The goal of robust optimization is that the solutions should remain feasible even if the input parameters of the model vary.
I know from Wikipedia (https://en.wikipedia.org/wiki/Robust_optimization) that there is also something called "Probabilistically robust optimization models". This can be bascially regarded as stochastic optimization so the borders between stochastic and robust optimization are not fully clear.
What are your takes on that? I'd appreciate every comment.