Meta-heuristics are methods used in solving optimization problems (OPs) in several areas. They follow some rules and instructions, and there is no learning from data in order to solve the OPs. When it comes to solving an optimization problem for the first time, we don't have any data that can be used, for example, to train a machine learning model, and this is the complicated part. So, how can we use machine learning to solve optimization problems?