搜索资源列表
GABOX
- 遗传算法实现TSP问题的工具箱程序，还包括大量遗传算法方面的实例，是很丰富的GA工具箱。-TSP problem genetic algorithm toolbox program also includes many examples of aspects of genetic algorithm, GA is a very rich toolbox.
GAMax
- 用遗传算法求二元函数的最大值，二元函数可以根据自己的需要更改。精度：0.001。 -Using GA to the maximum of the dual function, dual function can be changed according to their needs. Accuracy: 0.001.
ga
- 讲解如何用C语言实现遗传算法，以及应用遗传算法求解的全过程-Explain how to use C language implementation of genetic algorithms, and the application of genetic algorithm the whole process of
backpack-ga-algorithm
- 背包问题或0-1背包问题遗传算法程序，里面用的实数编码方式值得借鉴。-0-1 knapsack problem or knapsack problem genetic algorithm procedure, which uses real coding can be learned.
GA
- 遗传算法 0-1背包问题的代码 初始群体 选择 交叉 变异 评估函-0-1 knapsack problem genetic algorithm code for the initial assessment of functional group selection crossover and mutation
GA
- 遗传算法 解决最短路径 用C++来实现其功能 基于遗传算法的最短路径问题-Genetic algorithms to solve shortest path with C++ to achieve their function based on genetic algorithm shortest path problem
KZUIYF
- 关于遗传算法GA的相关内容介绍英文资料以及算法工具箱-Information about genetic algorithm GA related contents of introduction in English as well as the algorithm toolbox
09 遗传算法（Genetic Algorithm, GA）
- 遗传算法（Genetic Algorithm, GA）起源于对生物系统所进行的计算机模拟研究。它是模仿自然界生物进化机制发展起来的随机全局搜索和优化方法，借鉴了达尔文的进化论和孟德尔的遗传学说。其本质是一种高效、并行、全局搜索的方法，能在搜索过程中自动获取和积累有关搜索空间的知识，并自适应地控制搜索过程以求得最佳解。(The genetic algorithm (Genetic Algorithm, GA) originated from the computer simulation of b
bwjja
- 遗传算法(Genetic Algorithm,GA)是一种抽象于生物进化过程的基于自然选择和生物遗传机制的优化技术 遗传()