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【Mathimatics-Numerical algorithms】 Matlabcode DL : 0: 遗传算法，可实现多种选择和交叉、变异算法-Genetic algorithm, can realize a variety of selection and crossover and mutation algorithm
Update : 2024-05-04 Size : 11264 Publisher : 江伟
【Mathimatics-Numerical algorithms】 Guotao-algorithmic DL : 0: 线性非凸多父体杂交算子求解TSP问题。算法将搜索空间看成是一个全空间Ω，种群中的个体可以看作Ω中的一组向量。种群中的若干个向量构成一组基向量，它们可以张成Ω的一个子空间，这些向量随机性组合能相对均匀地搜索这一部分子空间。-Linear non-convex multi-parent crossover operator for solving TSP body problem. Algorithm search space as a full-space Ω, the individual populations can be considered as a set of vectors in Ω. The number of vector populations constitute a group of basis vectors, they can be a sub-space Ω Zhang, random combinations of these vectors could be relatively evenly Search this part of the sub-space.
Update : 2024-05-04 Size : 2048 Publisher : 李北辰
【AI-NN-PR】 yichuansuanfa_jixieshou DL : 0: 提出一种改进的遗传算法用于求解机械手运动学逆问题. 该算法采用实数编码, 其交叉概率和变异概率根据解的适应度函数值自适应调整. 计算机仿真结果显示, 该算法较简单遗传算法(SGA) 求解精度高, 收敛速度快且稳定性能好.-An improved genetic algorithm for solving the inverse problem of manipulator kinematics. The algorithm uses real number encoding, the crossover probability and mutation probability according to the fitness function value of solution adaptive. Computer simulation results show that the algorithm is relatively simple genetic algorithm for (SGA) for solving high precision, fast convergence and stable performance is good.
Update : 2024-05-04 Size : 143360 Publisher : 杨元龙
【AI-NN-PR】 GA DL : 0: 遗传算法求解函数最大值设计的种群规模，采用的选择算子，交叉概率，变异概率，进化代数和最优解-Design of population size, using the selection operator, crossover probability, mutation probability, evolutionary algebra and the optimal solution
Update : 2024-05-04 Size : 245760 Publisher : zsy
【Software Engineering】 GA DL : 0: C++ implementation of a Genetic algorithm (GA). A population of binary chromosomes is generated randomly to attempt to solve the Weighted MAX SAT Problem. Parameters of crossover, mutation, population size can be controlled via macros in code.There are text files for testing on.
Update : 2024-05-04 Size : 15215616 Publisher : MJ
【AI-NN-PR】 Genetic DL : 0: 遗传算法中，初始化，编码，解码，选择，交叉，变异，倒位的源程序-Genetic algorithms, initialization, encoding, decoding, selection, crossover, mutation, inversion of the source code
Update : 2024-05-04 Size : 9216 Publisher : 邓延丽
【matlab】 Ga DL : 0: 采用二进制Gray编码,采用基于轮盘赌法的非线性排名选择, 均匀交叉,变异操作,而且还引入了倒位操作. -Binary Gray encoding, roulette wheel method based on non-linear ranking selection, uniform crossover and mutation operations, but also introduces the inversion operation.
Update : 2024-05-04 Size : 3072 Publisher : lq
【AI-NN-PR】 genetic-algorithm-vc DL : 0: 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.
Update : 2024-05-04 Size : 310272 Publisher : 胡丹
【Other】 GA3 DL : 0: 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.
Update : 2024-05-04 Size : 13312 Publisher : 张瑞
【source in ebook】 360139 DL : 0: 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
Update : 2024-05-04 Size : 97280 Publisher : ABDELHEDI
【source in ebook】 SGA DL : 0: 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
Update : 2024-05-04 Size : 3072 Publisher : 李娟
【OS program】 tsp DL : 0: 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!
Update : 2024-05-04 Size : 11264 Publisher : yangshoping
【Program doc】 Solving DL : 0: 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 and non-numerical optimization methods (such as simulated annealing, genetic algorithms, etc.), genetic algorithm for solving approaches: the first on the top of the decision variable coding, on behalf of the were lower programming model, by solving the lower model of decision variables values into the upper model on behalf of the fitness value, and then crossover and mutation, select Options, and finally get the best solution.
Update : 2024-05-04 Size : 2048 Publisher : 大海
【Other】 SGA_C DL : 0: 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
Update : 2024-05-04 Size : 283648 Publisher : 王佳
【AI-NN-PR】 GA-1 DL : 0: 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++ language, output file format
Update : 2024-05-04 Size : 2048 Publisher : arrow
【AI-NN-PR】 geneticalgorithm DL : 0: 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
Update : 2024-05-04 Size : 2241536 Publisher : 王小玲
【Windows Develop】 code DL : 0: 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 individual is no difference between the fitness value. The system uses the rate selection, the essence of model, one point crossover and uniform mutation. If you replace the uniform mutation with Gaussian mutation, may be more effective.
Update : 2024-05-04 Size : 3072 Publisher :
【matlab】 cross DL : 0: 遗传算法分程序选择交叉变异源程序谢谢大家-GA selection crossover mutation
Update : 2024-05-04 Size : 2048 Publisher : 刘明
【Dialog_Window】 GoodPoint DL : 0: 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 section, another way of encoding decimal.
Update : 2024-05-04 Size : 1998848 Publisher : yangshoping
【Data structs】 GA DL : 0: 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
Update : 2024-05-04 Size : 2048 Publisher : 甘孟壮

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