遗传算法及其改进

本文首先对遗传算法的来源，基本原理，数学机理，特点及其应用进行了论述。这了提高遗传算法的收敛性能，同时考虑到交叉率和变异率的选取问题，本文简要介绍了一种基于个体适应度值的自适应调整交叉率和变异率的自适应遗传算法。

GENETIC ALGORITHM AND ITS MODIFICATION

In this paper, we first introduced and discussed in detail the Genetic Algorithm (GA) on its origin, its basic principle, its mathematics mechanism and its characteristics and application. In order to improve the convergence of GA, considering that it is difficult to choose the probability of crossover (Pc) and mutation (Pm), an Adaptive Genetic Algorithm (AGA) in which Pc and Pm were varied depending on the fitness values of the solutions was simply introduced. After analyzing its deficiency, a modified method Modified Adaptive Genetic Algorithm (MAGA) was presented in this paper. Finally, we compared the performance of the MAGA with those of the other methods using several optimization problems. Results showed that MAGA presented in this paper greatly improved the performance of convergence to the global optimum.