Generalized Nets (GN) are a tool for modelling of parallel processes. They represent an extension of the concept of Petri nets and the rest of their modifications. In a series of books, generalized nets have been shown as a uniform language for description of various concepts and paradigms from the area of artificial intelligence. During the last 15 years, different types of genetic algorithms have been introduced. In the present book, GN-models for some of them are developed. These GN-models describe the functions and the results of various separate genetic algorithms.