It can solve every optimisation problem which can be described with the chromosome encoding.
It solves problems with multiple solutions.
Since the genetic algorithm execution technique is not dependent on the error surface, we can solve multi-dimensional, non-differential, non-continuous, and even non-parametrical problems.
Structural genetic algorithm gives us the possibility to solve the solution structure and solution parameter problems at the same time by means of genetic algorithm.
Genetic algorithm is a method which is very easy to understand and it practically does not demand the knowledge of mathematics.
Genetic algorithms are easily transferred to existing simulations and models.