搜索资源列表
genetic-algorithm-vc
- 用VC实现的遗传算法的完整工程文件。有转轮法，交叉和变异。-VC genetic algorithm implemented with the full project file. There wheel method, crossover and mutation.
GA3
- 遗传算法--函数最优化任意随机交叉父体。在遗传算法中引入任意随即交叉概念，增加个体多样性。-Genetic algorithms- function is to optimize the parent body of arbitrary random crossover. The introduction of any genetic algorithm is then cross-concept, increase the diversity of individuals.
360139
- In this paper, an attractive approach for teaching genetic algorithm (GA) is presented. This approach is based primarily on using MATLAB in implementing the genetic operators: crossover, mutation and selection
SGA
- 基本遗传算法代码实现，选择交叉变异 对于初学遗传算法的同志很有帮助，希望大家一起提高进步-Code to achieve the basic genetic algorithm, select the crossover and mutation genetic algorithm for beginners comrades helpful, hope all of us to improve progress
tsp
- 该程序解决10个城市的货郎担问题（TSP），主要使用简单的遗传算法实现。该过程中包括：编码、解码，选择，交叉，变异等！-The program to solve the traveling salesman problem of 10 cities (TSP), the use of simple genetic algorithm. The process includes: encoding, decoding, selection, crossover and mutation!
Solving
- 求解双层规划问题常用的算法有极点算法、直接搜索法、下降法和非数值优化方法(如模拟退火算法、遗传算法等)，遗传算法的求解思路是：首先对上层的决策变量编码，代人下层规划模型，通过求解下层模型的决策变量值，代入上层模型计算适应度值，然后进行交叉、变异、选择操作，最后求出最优解。-Solving Bilevel Programming Problems with pole algorithm commonly used algorithms, direct search method, descent
SGA_C
- 基本遗传算法的实现，包括简单的交叉，变异操作-Basic genetic algorithm, including the simple crossover and mutation operators
GA-1
- 遗传算法求解函数极值问题。完整实现了遗传算法的选择/交叉/变异等功能，可设定交叉和变异概率。C++语言，输出为文件形式-Genetic Algorithm for function extremum problem. Full realization of the genetic algorithm selection/crossover/mutation and other functions, can be set crossover and mutation probability. C+
geneticalgorithm
- 典型遗传算法的具体实现过程，包括 选择算子 交叉算子 变异算子的 选择方法-Concrete realization of a typical genetic algorithm process, including selection operator crossover mutation operator selection method
code
- 注意代码 的设计是求最大值，其中的目标函数只能取正值；且函数值和个体的适应值之间没有区别。该系统使用比率选择、精华模型、单点杂交和均匀变异。如果用 Gaussian变异替换均匀变异，可能得到更好的效果。-Note that the code is designed to seek maximum value, in which the objective function can only take positive and the function value and the individ
cross
- 遗传算法分程序 选择交叉变异源程序 谢谢大家-GA selection crossover mutation
GoodPoint
- 使用佳点集遗传算法，解决安徽十七市的TSP问题，求出最短路径主要区别于普通遗传算法的地方是染色体交叉部分，另外编码方式使用十进制方式。-Good point set genetic algorithm used to solve TSP problem the city of Anhui, 17, find the shortest path to the main place is different from ordinary genetic algorithm is crossover s
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
GAsuanfa
- 此程序通过遗传算法(GA)实现灰度图像的分割,遗传算法的计算过程首先是将实际的优化问题编码成符合串,也称码串、染色体。将实际问题的目标函数转变为染色体的适应函数,然后在随机产生的一批初始染色体的基础上,根据各染色体的适应函数值进行繁殖、交叉、变异等遗传操作产生下一代染色体。 -This procedure of genetic algorithm (GA) to achieve gray scale image segmentation, genetic process of the algor
traveling_salesman
- 遗传算法 旅行商路径优化 编码选择交叉变异解码-Genetic algorithm optimization of traveling salesman path selection crossover and mutation encoding decoding
Simple-genetic-algorithm-source-code
- 这是一个非常简单的遗传算法源代码，是由Denis Cormier (North Carolina State University)开发的，Sita S.Raghavan (University of North Carolina at Charlotte)修正。代码保证尽可能少，实际上也不必查错。对一特定的应用修正此代码，用户只需改变常数的定义并且定义“评价函数”即可。注意代码 的设计是求最大值，其中的目标函数只能取正值；且函数值和个体的适应值之间没有区别。该系统使用比率选择、精华模型、单点杂
AGA
- 介绍一种改进传统遗传算法的新方法，通过调节交叉概率和变异概率-Introduction of a new genetic algorithm to improve the traditional method, by adjusting the crossover probability and mutation probability
Genetic-Algorithms
- 这是一个简单的ＧＡ源代码，该系统使用比率选择、精华模型、单点交叉和均与变异-This is a simple GA source code, the system uses the rate selection, the essence of model, and both single-point crossover and mutation
GA
- 这是一个简单遗传算法，包括初始化群体、选择、交叉、变异，结果可以输出到文本文档-This is a simple genetic algorithm, including the initialization population, selection, crossover and mutation, the results can be exported to a text document
GA_test
- 遗传算法：二进制、单点交叉、单点变异、轮盘赌、模拟退火(默认无)、最优个体保留(默认无)-Genetic algorithm: binary, single-point crossover, single-point mutation, roulette, simulated annealing (default no), best individual reservations (default no)