改进遗传算法－郭涛算法做最优化问题很管用,算法的基本思想是

先任意产生n个随机数，然后从n个数里随机选择m个数，再有这m个

数合成一个新数，将这个新数同n个数中间适应值函数值的最差的比较，

如果好的话就取代最差的那个，如果它比最好的还要好的话，则把最好的

也取代。如果比最差的坏，则重新合成一个新数。依次循环下去。

-improved genetic algorithm - Guo Tao algorithm optimization is the most effective. Algorithm for the basic idea is to have arbitrary n random number and then the number n m Lane randomly selected number, This again is an m number of new synthesis of the new middle with n number of fitness function of the worst, If good to replace the worst, um, if it is even the best than good, it serves the best have replaced. If worse than the worst, the re-synthesis of a new number. Followed the cycle continues.