文件名称:改进遗传算法－郭涛算法做最优化问题很管用
- 所属分类：
- 人工智能/神经网络/遗传算法
- 资源属性：
- [Text]
- 上传时间：
- 2012-11-26
- 文件大小：
- 2kb
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- 0次
- 提 供 者：
- 龚**
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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。
程序的奇妙之处是GA_crossover()函数，产生的新数确实比较好，看看
那位大侠能改进一下，产生比这跟好的数。-improved genetic algorithm- Guo Tao done optimization algorithm is very effective, and the algorithm is the first basic idea arbitrary n generated random number and then the number li n m randomly selected number, and this number m of a new synthesis of the new middle with n number fitness function of the worst by comparison, if a good case to replace the worst, um, if it even than the best, then ruled the best have replaced. If worse than the worst, a de novo synthesis of new. Followed by the cycle continues. The magic of procedures is GA_crossover () function, the new really good to see heroes who can be improved upon, it generated more than a few with a good.
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。
程序的奇妙之处是GA_crossover()函数，产生的新数确实比较好，看看
那位大侠能改进一下，产生比这跟好的数。-improved genetic algorithm- Guo Tao done optimization algorithm is very effective, and the algorithm is the first basic idea arbitrary n generated random number and then the number li n m randomly selected number, and this number m of a new synthesis of the new middle with n number fitness function of the worst by comparison, if a good case to replace the worst, um, if it even than the best, then ruled the best have replaced. If worse than the worst, a de novo synthesis of new. Followed by the cycle continues. The magic of procedures is GA_crossover () function, the new really good to see heroes who can be improved upon, it generated more than a few with a good.
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改进遗传算法－郭涛算法做最优化问题很管用.txt