An improved genetic algorithm and its application

genetic algorithms;  fault-tolerant system;  Optimize the model

Due to its hidden row and global search characteristics, the genetic algorithm has advantages that other conventional optimization algorithms cannot have. However, the standard genetic algorithm has shortcomings such as slow convergence speed and easy "precocious puberty". In view of the limitations of the standard genetic algorithm, the design of the genetic algorithm is improved from many aspects, such as adaptation value, crossover and variation operators, and selection of control parameters. This improved genetic algorithm can further improve the search ability, search efficiency and convergence performance of the algorithm. Finally, the optimization model of (N+M) customer-error system is taken as the optimization goal, and the optimal solution of the cost model is obtained. The calculation results verify the validity and correctness of the algorithm.