Application on Express Delivery of an Immune Genetic Algorithm Based on Machine Learning
Chang Zheng, Zhu Guang-Ming · 2009
A new set of immune genetic algorithm is designed to solve express delivery path optimization problem, which introduces static propagation principle and machine learning theory to the immune genetic algorithm. Using adaptive vaccines, enhance individual immunity, and increase the average fitness value of stocks, so as to effectively prevent the loss of the optimal solution to narrow the search space, making the speed of evolution speeded up, enabling the system to get the optimal solution in a very short time. After verification, the algorithm is much higher accuracy than the simple genetic algorithm, and the number of iterations to get a stable solution is significantly reduced.