Description: 遗传算法源代码,实现了选择操作、交叉操作和变异操作，通过适应度函数完成种群的选择及收敛。-genetic algorithm source code and realized the choice of operation, crossover and mutation operation, through fitness function completed Stocks choice and convergence. Platform: |
Size: 30590 |
Author:李文 |
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Description: 遗传算法源代码,实现了选择操作、交叉操作和变异操作，通过适应度函数完成种群的选择及收敛。-genetic algorithm source code and realized the choice of operation, crossover and mutation operation, through fitness function completed Stocks choice and convergence. Platform: |
Size: 30720 |
Author:李文 |
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Description: 基于改进后的遗传算法 交叉、变异操作后，在windows平台下用C语言实现求解TSP问题-Based on the improved genetic algorithm crossover and mutation operation, in windows platform using C language for solving TSP problems Platform: |
Size: 3072 |
Author:lc |
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Description: 遗传算法求解极值的源程序，只需将要求函数在源文件中输入，即可，种子数100，变异概率和交叉概率可调-Extremes of genetic algorithm source code, simply will be asked to function in the source file type, you can, seed number of 100, mutation probability and crossover probability adjustable Platform: |
Size: 540672 |
Author:stefwang |
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Description: maltab遗传算法源程序，此程序为一个一个的小程序分开的，很完整。包括编码，设定初始种群，交叉，变异，及结束条件等-maltab genetic algorithm source code, this procedure a small as a separate process, it is complete. Including encoding, set the initial population, crossover and mutation, and the end conditions Platform: |
Size: 7168 |
Author:joean |
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Description: 遗传算法源代码,实现了选择操作、交叉操作和变异操作，通过适应度函数完成种群的选择及收敛.-Genetic algorithm source code, to achieve the selection operation, crossover operation and mutation operation, through the completion of the fitness function the choice of populations and convergence. Platform: |
Size: 10240 |
Author:易志成 |
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Description: 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。代码没有任何图形，甚至也没有屏幕输出，主要是保证在平台之间的高可移植性。读者可以从ftp.uncc.edu, 目录 coe/evol中的文件prog.c中获得。要求输入的文件应该命名为‘gadata.txt’；系统产生的输出文件为‘galog.txt’。输入的 文件由几行组成：数目对应于变量数。且每一行提供次序——对应于变量的上下界。如第一行为第一个变量提供上下界，第二行为第二个变量提供上下界，等等。 -It is a very simple genetic algorithm source code, is Denis Cormier (North Carolina State University) developed, Sita S. Raghavan (University of North Carolina at Charlotte) amendment. Code to ensure as little as possible, in fact, do not have to troubleshooting. The application of a specific amendment to this code, the user simply changes the definition of constants and the definition of "evaluation function" can be. 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, single-point crossover and uniform mutation. If you replace the uniform mutation with Gaussian mutation, may be more effective. Code without any graphic or even no screen output, mainly to ensure a high portability between platforms. Readers can ftp.uncc.edu, directory coe/evol file prog.c obtained. Required input file sho Platform: |
Size: 8192 |
Author:李礼 |
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Description: 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。代码没有任何图形，甚至也没有屏幕输出，主要是保证在平台之间的高可移植性。读者可以从ftp.uncc.edu, 目录 coe/evol中的文件prog.c中获得。要求输入的文件应该命名为‘gadata.txt’；系统产生的输出文件为‘galog.txt’。输入的 文件由几行组成：数目对应于变量数。且每一行提供次序——对应于变量的上下界。如第一行为第一个变量提供上下界，第二行为第二个变量提供上下界，等等。 -This is a very simple genetic algorithm source code, by Denis Cormier (North Carolina State University) developed, Sita S. Raghavan (University of North Carolina at Charlotte) amendment. Code to ensure that as little as possible, in fact, do not have to troubleshoot. The application of a specific amendment to this code, the user simply changes the definition of constants and the definition of "evaluation function" button. Note that the code is designed to seek maximum value, where 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 ratio of choice, the essence of model, single-point crossover and uniform mutation. If you replace the uniform mutation with Gaussian mutation, may get better results. Code without any graphic or even no screen output, mainly to ensure a high portability between platforms. Readers can ftp.uncc.edu, directory coe/evol file prog.c obtained. Requires the input f Platform: |
Size: 5120 |
Author:qinjian |
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Description: 遗传算法是一种进化算法，应用广泛，此文件包含基本遗传算法，顺序选择遗传算法，适值函数标定的遗传算法，大变异遗传算法，自适应遗传算法，双切点交叉遗传算法，多变异位自适应遗传算法matlab源代码，供大家参考-Genetic algorithm is an evolutionary algorithm, widely used, this file contains the basic genetic algorithm, genetic algorithm selection order coincided with the genetic algorithm calibration function, a large variation of genetic algorithm, adaptive genetic algorithm, two-cut point crossover genetic algorithm, variable ectopic Adaptive genetic algorithm matlab source code for your reference
Platform: |
Size: 6144 |
Author:熊杰 |
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Description: 自然计算中遗传算法的各个程序，matlab环境下开发的源代码。best.m 求种群中适应度最大的值
calfitvalue.m 计算每个个体的适应度
calobjvalue.m 适应度函数
crossover.m 交叉变换
decodebinary.m 将二进制数转换成十进制数
decodechrom.m 将二进制数转换成十进制数
initpop.m 产生初始种群
mutation.m 变异
selection.m 选择合适的个体进行复制
main.m 主函数
-Nature of each genetic algorithm calculation procedures, matlab environment with source code. best.m find the largest population in the fitness value of calfitvalue.m calculated for each individual' s fitness calobjvalue.m fitness function crossover.m cross-conversion decodebinary.m Converts a binary number into decimal number decodechrom.m Converts a binary number into decimal number initpop.m generate initial population mutation.m variation selection.m select the appropriate individual to copy main.m primary function Platform: |
Size: 3072 |
Author:王芳 |
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Description: 遗传算法的matlab源代码，包含了从基本遗传算法到，自适应，多种交叉方式等遗传算法的源代码-Genetic algorithm of matlab source code, including from the basic genetic algorithm to, adaptive, a variety of crossover modes and genetic algorithm of source code
Platform: |
Size: 8192 |
Author:lzyacht |
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Description: 本文件含论文及源代码。论文首先介绍了基本遗传算法的基本原理、特点及其基本实现技术，接着针对背包问题，论述了遗传算法在编码表示和遗传算子（包括选择算子、交叉算子变异算子这三种算子）等方面的应用情况。并且结合背包问题实例，给出了具体的编码方法，运行参数，群体大小，最大迭代次数，以及合适的遗传算子。最后，简单说明了遗传算法在求解背包问题中的应用并对遗传算法解决背包问题的前景提出了展望。-The file containing the papers and source code. The paper first introduces the basic principles of the basic genetic algorithm, the characteristics of its basic implementation techniques, and then for the knapsack problem, discusses the genetic algorithm coded representation and genetic operators (including selection operator, crossover operator mutation operator three count sub), and other aspects of the application. And the combination of an instance of the knapsack problem, given specific encoding method, operating parameters, population size, maximum number of iterations, and appropriate genetic operators. Finally, a brief description of the genetic algorithm Knapsack problem and genetic algorithm to solve the knapsack problem prospects prospect. Platform: |
Size: 420864 |
Author:李海波 |
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Description: 基于MATLAB的遗传算法的源程序,内含交叉变异等多种方式的源码。-Based on MATLAB genetic algorithm source code, including crossover and mutation of the source of a variety of ways. Platform: |
Size: 112640 |
Author:章丽 |
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Description: 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。代码没有任何图形，甚至也没有屏幕输出，主要是保证在平台之间的高可移植性。读者可以从ftp.uncc.edu,目录 coe/evol中的文件prog.c中获得。要求输入的文件应该命名为‘gadata.txt’；系统产生的输出文件为‘galog.txt’。输入的文件由几行组成：数目对应于变量数。且每一行提供次序——对应于变量的上下界。如第一行为第一个变量提供上下界，第二行为第二个变量提供上下界，等等。-This is a very simple genetic algorithm source code, by Denis Cormier (North Carolina State University) developed, Sita S.Raghavan (University of North Carolina at Charlotte) corrected. Code to ensure as little as possible, in fact, do not have to troubleshoot. For a specific application fix this code, users only need to change the definition of constants and the definition of "evaluation function" button. Note that the code is designed for the maximum, in which the objective function can only take positive values , and fitness function values and the individual is no difference between the values . The system uses the ratio selection, the essence of the model, a single point crossover and uniform mutation. If you replace the uniform mutation with Gaussian mutation may get better results. Code has no graphics, or even no screen output, mainly to ensure high portability between platforms. Readers can ftp.uncc.edu, catalog coe/evol files prog.c ge Platform: |
Size: 35840 |
Author:周成 |
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Description: 旅行商问题(TSP)是典型的NP完全问题，遗传算法是求解NP完全问题的一种常用方法。旅行商问题(TSP)的蚁群算法实现算法。在MATLAB中用遗传算法施行对TSP问题进行了求解，进行了选择、交叉和变异算子进行了算法设计。MATLAB源代码。-Traveling Salesman Problem (TSP) is a typical NP-complete problem, genetic algorithm for solving NP-complete problems, a common method. Traveling Salesman Problem (TSP) ant colony algorithm. Implemented in MATLAB using genetic algorithms to solve the TSP problem, a selection, crossover and mutation operators of the algorithm design. MATLAB source code. Platform: |
Size: 2048 |
Author:申悦 |
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Description: 多目标整数规划的遗传算法NSGA-IImatlab源代码，主程序、初始化、计算适应度、排序、选择、交叉变异、重组，最后得到Pareto前言。可以跑通，下载即用，具体方法介绍博客上文章上都有。-Multi-objective integer programming genetic algorithm NSGA-IImatlab source code, the main program, initialization, calculate fitness, sorting, selection, crossover and mutation, recombination, and finally get Pareto foreword. You can run through, downloading, using the specific method described has an article on the blog. Platform: |
Size: 12288 |
Author:hanhe |
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Search - genetic algorithm crossover source code