搜索资源列表
grid_method
- 优化设计算法：用1维格点法求目标函数的最优解和最优值，已经验证算法的正确性，visual C++6.0开发-Optimization algorithm: 1 Dimensional grid Method with the objective function of the optimal solution and optimal value, has verified the correctness of the algorithm, visual C++6.0 development
golden_section
- 优化设计算法：用黄金分割法求目标函数的最优解和最优值，已经验证算法的正确性，visual C++6.0开发-Optimization algorithm: The Golden Section Method objective function of optimal solution and optimal value, has verified the correctness of the algorithm, visual C++6.0 development
Differential_Evolution
- 优化设计算法：用微分进化法求目标函数的最优解和最优值，已经验证算法的正确性，visual C++6.0开发-Optimization Algorithm: Differential Evolution Method with the objective function of the optimal solution and optimal value, has verified the correctness of the algorithm, visual C++6.0 developmen
simplex
- 优化设计算法：用单纯形法求解目标函数的最优解和最优值，已经验证算法的正确性，在visual c++6.0下开发-Optimization algorithm: the simplex method with the optimal solution of objective function and the optimal value, has verified the correctness of the algorithm in visual c++6.0 under development
powell
- 优化设计算法：用powell法求解目标函数的最优解和最优值，已经验证算法的正确性，在visual c++6.0下开发-Optimization algorithm: Solving the objective function with powell optimal solution and optimal value, has verified the correctness of the algorithm, the visual c++6.0 under development
PSO
- 本程序是原始粒子群算法，对一个简单函数的优化，可用来与其他算法功能进行比较。-This procedure is the original particle swarm optimization, a simple function of the optimization function can be used to compare with other algorithms.
dimension_turn_6
- 优化设计算法：用坐标轮换法求目标函数的最优解和最优值，已经验证算法的正确性，visual C++6.0开发，变量维数为6 -Optimization Algorithm: Method using coordinate rotation objective function of optimal solution and optimal value, has verified the correctness of the algorithm, visual C++6.0 developmen
Unconstrainedoptimizationofcontinuousfunctionofart
- 此源码是对人工蚁群算法的一种实现，用于无约束连续函数的优化求解，对于含有约束的情况，可以先使用罚函数等方法，把问题处理成无约束的模型，再使用本源码进行求解。-This source code is an implementation of artificial ant colony algorithm for unconstrained continuous function optimization, with constraints for the case, you can start u
pso_2D
- 使用微粒群算法进行对目标函数进行优化的m文件源码-Using the particle swarm algorithm to optimize the objective function m-file source
code
- 该程序包包括了matlab 优化工具箱里函数的介绍及具体实例。有一个配套使用的视频教程，在优酷里搜索“matlab 优化工具箱入门经典教程”。希望对学习优化算法的有用。 -The package includes the matlab optimization toolbox function descr iption and specific examples. Supporting the use of a video tutorial, the excellent Cool Search
BFGS
- 最近学习优化理论中的算法，通过网上的查找及改进，得到了共轭梯度法的C语言程序 主要问题：如函数为f(X)=x1*x1*x1*x1+x2*x2时，算得的结果有问题，初步估计是因为迭代公式中出现了求梯度的模的分量造成的，有待继续改进，不过用BFGS算法C语言程序算时，上述问题没有发生，所以才说BFGS算法是无约束优化中最稳定的算法之一了-Optimization theory in a recent study of algorithms, through online search and i
GA
- 遗传算法，对一个函数进行优化的。以求得函数的极值。-GA
Target
- 关于目标函数的算法，通过遗传算法优化，使目标简化-On the objective function of the algorithm, genetic algorithm, the target simplifies
PSO
- 在判别分析中使用粒子群优化算法求解最优判别函数-Particle Swarm Optimization(PSO)
yichuansuanfa
- 用该遗传算法程序解决多峰值函数的优化问题，输出结果和图形！-Using the genetic algorithm program to solve the optimization problem of multi-peak function, output and graphics!
MAPv1
- 关于memetic算法的源码，对各种函数进行了优化，希望对这个研究方向感兴趣的人能够共同交流-Memetic algorithm on the source code has been optimized for a variety of functions, in the hope that people interested in research to work together to communicate
prog1013
- web服务选择优化算法，采用单纯性改进算法来实现。效率优于matlab原始库函数。-web service selection algorithm, improved algorithm using simple to achieve. Efficient than the original matlab library function.
genetic_algorithm
- 用遗传算法进行简单函数的优化,有具体的函数描述及说明-the optimization of simple function by using genetic algorithm
multi-ctp1
- 一个基于阈值的粒子比较准则，用于处理多目标约束优化问题,该准则可以保留一部分序值较小且约束违反度在允许范围内的不可行解微粒,从而达到由不可行解向可行解进化的目的；一个新的拥挤度函数,使得位于稀疏区域和Pareto前沿边界附近的点有较大的拥挤度函数值,从而被选择上的概率也较大 从而构成解决多目标约束优化问题的混合粒子群算法。-A comparison based on the threshold criteria for the particle to handle multi-objective
yichuansuanfahanshuyouhua
- 对遗传算法思想的理解和认识,对一个函数求其最小值，采用遗传算法的交叉，变异等特征进行优化求解-Genetic algorithms for understanding and awareness of thoughts, seeking the minimum of a function, using genetic algorithm crossover and mutation characteristics of the optimal solution