Description: LinPacker是一个优化矩形布局的工具，是在具有遗传算法的半无限大小区完成这一操作的。对缩减工厂的库存是有用的。-LinPacker optimization is a rectangular layout of the tool, with a genetic algorithm in the semi-infinite size of the area to complete the operation. To reduce factory stocks will be useful. Platform: |
Size: 9216 |
Author:苏明春 |
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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: 免疫遗传算法matlab 程序,该算法由抗原识别、初始抗体产生、适应度计算、向记忆细胞分化、抗体的促进和抑制、抗体产生(交叉、变异) 六个模块组成-immune genetic algorithm Matlab procedure, the algorithm by antigen identification, initial antibody, fitness, to the memory cells, antibody for the promotion and inhibition, antibody (crossover and mutation) six modules Platform: |
Size: 1024 |
Author:He Hong |
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Description: 这个是用遗传算法实现的最优路径规划，经本人验证完全可以实现，能够出图。-This is a genetic algorithm is used to realize the optimum path planning, as I can verify that the realization of a plan to. Platform: |
Size: 4096 |
Author:qushaohua |
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Description: 基于遗传算法的人工生命模拟,用VC++编写，对于理解遗传算法有好处-Based on genetic algorithm artificial life simulation, using VC++ to prepare, good for understanding the genetic algorithm Platform: |
Size: 8192 |
Author:刘长乐 |
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Description: 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. Platform: |
Size: 310272 |
Author:胡丹 |
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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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Description: 遗传算法在MATLAB环境中的实现,适合图形模式识别广泛应用等方面-Genetic algorithm implementation in MATLAB environment, suitable for wide range of graphics applications such as pattern recognition Platform: |
Size: 77824 |
Author:zhx |
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Description: 用遗传算法求解TSP问题，包含选择，交叉，变异算子。迭代效率较高(The genetic algorithm is used to solve the TSP problem, including selection, crossover and mutation operators. The iterative efficiency is higher) Platform: |
Size: 258048 |
Author:andycorleone
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