Description: 这是本人在做硕士论文时设计的遗传算法工具箱代码-this is my master's thesis done at the design of the genetic algorithm code Toolbox Platform: |
Size: 1024 |
Author:曾海莹 |
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Description: 遗传算法接口代码,可根据实际问题调用里边的函数。-genetic algorithm interface code, according to actual problems along the calling function. Platform: |
Size: 4096 |
Author:郑军 |
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Description: 遗传算法，里面分为4个部分，第一，二部分主要是看sexual reproduction 和asxuel reproduction的区别。第三部分里面有spatial 和 non-spatial的比较。第4部分是遗传算法中有关modularity 的相关代码。-Genetic algorithm, which is divided into four parts, the first and second is to look at some of the major sexual reproduction and the difference between asxuel reproduction. Part III there are spatial and non-spatial comparison. Part 4 is a genetic algorithm on the modularity of the relevant code. Platform: |
Size: 76800 |
Author:陈坚生 |
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Description: 遗传算法求解01背包问题＋实验报告＋参考文献。如果你看了这个程序还是不能明白遗传算法的巧妙，那么还是不要再看这个问题了。-Genetic Algorithm for Knapsack Problem 01 experimental report references. If you read this procedure should not understand the genetic algorithm or clever, then it is better not to look at this issue. Platform: |
Size: 201728 |
Author:gouyabin |
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Description: 这是自适应遗传算法的MATALB代码,经调试运行通过,希望对大家有用-This is self-adaptive genetic algorithm MATALB code, adopted by the debugger to run, everyone would like to be useful Platform: |
Size: 5120 |
Author:liyan |
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Description: 传算法伪代码实例，遗传算法中最重要的过程就是选择和交叉。 -Examples of pseudo-code algorithm, genetic algorithm is the most important process of selection and crossover. Platform: |
Size: 1024 |
Author:何炎雯 |
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Description: 基于遗传算法的研究的代码，利用的是C语言描述-Research based on genetic algorithm code, using the C language to describe Platform: |
Size: 9093120 |
Author:张扬 |
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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: 基于新的树编码方式用免疫遗传算法解决DCMST问题：提出了一种新的树编码方式，可以方便地表达一棵树，简化了树在遗传算法中的编码表达。且新的树编码方式清楚地表达了边的信息，有利于疫苗的设计。此外，本文使用免疫遗传算法，有效地克服了传统遗传算法中解退化的现象。数值实验表明，解的振荡相对于传统遗传算法减小了，且收敛速度更快。-New tree-based encoding genetic algorithm with immune DCMST problem: A new tree encoding, you can easily express a tree, the tree simplifies the code in the expression of genetic algorithm. And new tree encoding side clearly expressed information is conducive to vaccine design. In addition, we use the genetic algorithm can effectively overcome the traditional genetic algorithm, the phenomenon of degradation in the solution. Numerical experiments show that the oscillation of solutions with respect to reducing the traditional genetic algorithm, and the convergence faster. Platform: |
Size: 5120 |
Author:LYC |
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Description: 遗传算法车间调度,车间作业调度问题遗传算法
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输入参数列表
M 遗传进化迭代次数
N 种群规模(取偶数)
Pm 变异概率
T m×n的矩阵，存储m个工件n个工序的加工时间
P 1×n的向量，n个工序中，每一个工序所具有的机床数目
输出参数列表
Zp 最优的Makespan值
Y1p 最优方案中，各工件各工序的开始时刻，可根据它绘出甘特图
Y2p 最优方案中，各工件各工序的结束时刻，可根据它绘出甘特图
Y3p 最优方案中，各工件各工序使用的机器编号
Xp 最优决策变量的值，决策变量是一个实数编码的m×n矩阵
LC1 收敛曲线1，各代最优个体适应值的记录
LC2 收敛曲线2，各代群体平均适应值的记录
最后，程序还将绘出三副图片：两条收敛曲线图和甘特图（各工件的调度时序图）-Genetic algorithm scheduling, job shop scheduling problems with genetic algorithms -------------------------------------------------------------------------- genetic evolution of the input parameter list, the number of iterations M N population size (taken even) Pm mutation probability T m × n matrix, stored m one piece n a process of processing time 1 × n vector, n a process in which each machine processes the number of Zp with the best value Y1p Optimal Makespan programs, the start time of each process the workpiece can be drawn based on its optimal solution Gantt Y2p, each time the workpiece end of the process, according to its draw Gantt Y3p optimal solution, each piece of the processes using machine code Xp optimal decision variable, decision variable is a real m × n matrix encoded LC1 convergence curve 1, the generation of the best individual record of LC2 fitness convergence curve 2, the average fitness value on behalf of groups record Finally, the program will draw three pict Platform: |
Size: 2048 |
Author:王龙隐 |
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Search - Genetic Algorithm code