基于优化遗传算法的软硬件划分方法

针对软硬件划分问题，研究了一种优化的遗传算法，提出硬件倾向度的概念，用于遗传算法初始群体的生成，减少了初始解的随机性和搜索的盲目性；在遗传算法过程中，使交叉变异概率随着遗传过程由大变小，保证早期具有较大的搜索空间，后期又能保留较好的解，使用动态结束条件自适应结束遗传算法。与对比算法相比，该算法的效率较高，且在大规模问题求解上能够获得更优解。

Hardware and software partitioning method

For hardware and software partitioning problem, a kind of genetic algorithm optimization, the concept of hardware tendency degree of genetic algorithm used to generate the initial population, reducing the randomness and blindness searching initial solution; genetic algorithm process, so that the probability of crossover and mutation genetic processes from large to small as to ensure early with a larger search space, and also allows the latter to retain a better solution, end the use of dynamic adaptive genetic algorithm end condition. Compared with the comparison algorithm, the higher the efficiency of the algorithm and problem solving on a large scale problem can get better solutions.