Genetic Algorithm (GA) was first put forward by John holland of the United States in 1970s, and it was designed and put forward according to the evolution law of creatures in nature. It is a computational model to simulate the natural selection and genetic mechanism of Darwin's biological evolution theory, and it is a method to find the optimal solution by simulating the natural evolution process.

The basic operation process of genetic algorithm is as follows:

(1) initialization: set the evolutionary algebra counter t=0, set the maximum evolutionary algebra t, and randomly generate m individuals as the initial population P(0).

(2) Individual evaluation: calculate the fitness P(t) of each individual in the population.

(3) Selection operation: the selection operator is applied to the population. The purpose of selection is to pass the optimized individuals directly to the next generation, or to produce new individuals through pairing and crossover, and then pass them on to the next generation. The selection operation is based on the adaptability evaluation of individuals in the group. ?

(4) crossover operation: crossover operator is applied to population. Crossover operator is the core of genetic algorithm.

(5) mutation operation: mutation operator is applied to population. That is, changing the gene value of some loci in a single string in a population. After the selection, crossover and mutation of population P(t), the next generation population P(t+ 1) is obtained. ?

(6) Judgment of termination condition: if t=T, the individual with the greatest fitness obtained in the evolution process is output as the optimal solution, and the calculation is terminated.