搜索资源列表
pso
- This an implementation of Particle Swarm Optimization algorithm using the same syntax as the Genetic Algorithm Toolbox, with some additional options specific to PSO. Allows code-reusability when trying different population-based optimization al
GA
- 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
GA_test1_2
- Genetic algorithm , It is about cross over , mutation ,, roulette wheel
GA
- 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 a
Genetic
- 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
mann-kendalltubianfenxi
- mann-kendall突变点分析，vb应用程序，简单-mann-kendall mutation point analysis, vb application, a simple
Ga
- 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.
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.
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
BGA
- 题目：非平稳时间序列突变检测的启发式分割算法（BG算法） 本源码实现了下面参考文献中的算法，并对该文献中的实例进行了仿真-Title: Non-stationary time series mutation detection heuristic segmentation algorithm (BG algorithm) of the source references to achieve the following algorithm, and examples of the liter
BMDCP
- 突变分为如下主要的几种：均值突变（最常见）、方差突变、线性回归突变（也称趋势突变）、概率突变、空间型突变、谱突变、模型参数突变，等等。贝叶斯突变检测属于概率突变检测方法，其特点是能给出突变点的概率分布图。-Mutations are divided into the following main categories: the mean mutation (the most common), variance mutation, linear regression mutation (also
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
TSP
- 遗传算法，可以实现遗传算法TSP优化，图形显示优化过程。可以设定遗传种群个数、变异率等参数。-Genetic algorithm, genetic algorithm can achieve TSP optimization, graphics optimization process. Can set the number of genetic populations, mutation rates and other parameters.
IGA
- 为改进遗传算法的源程序，采用了多次2-opt变异算子，进一步改进了计算结果。-The source code for the improved genetic algorithm using a number of 2-opt mutation operator to further improve the results.