Introduce a Specific Process of Genetic Algorithm through an Example

Genetic algorithm is a kind of evolutionary algorithm. It searches for the optimal solution by mimicking the choice of nature and the mechanism of genetics. Genetic algorithm has three basic operators: selection, crossover and mutation. The main method of numerical method for solving NP problem is an iterative operation. The general iterative method is easy to fall into the local minimum trap and the "infinite loop" phenomenon and making the iteration impossible. The genetic algorithm overcomes this short coming and is a global optimization algorithm. This paper studies the algorithmic process of genetic algorithm, introduces the specific genetic process of genetic algorithm through an example, and finally summarizes the advantages and disadvantages of genetic algorithm. In the analysis of disadvantages of genetic algorithms, we must develop better method to avoid its weaknesses. The purpose is to find a better combination algorithm to overcome the shortcomings of genetic algorithms and to exploit the advantages of genetic algorithms.