搜索资源列表
禁忌搜索算法实现蚁群繁殖问题算法
- 采用禁忌算法实现的蚁群繁殖算法，该问题可以很好地解决蚁群问题中优化问题-taboo algorithm using the Ant Algorithm breeding, the problem can be successfully resolved ant colony optimization problems
DGPSO.rar
- 用于求解约束优化问题的算法，算法为差分进化/遗传算法/微粒群算法的融合。对于“[7] T. P. Runarsson and X. Yao, Stochastic ranking for constrained evolutionary optimization, IEEE Trans. Evol. Comput., vol. 4, no. 3, pp. 284-294, Sep. 2000”中给出的13个标准测试函数，均能得到问题最优解。如有任何疑问，请于http://2shi.phphube
psoprogress.rar
- ％程序名称：求解约束优化问题的改进粒子群优化算法 ％程序功能：求解带各种约束条件的优化问题 ％输入条件：各种初始条件，以及设定参数 ％输出数值：最优解位置以及函数极小值 , Program name: for solving constrained optimization problems to improve particle swarm optimization algorithm program features: solving with a variety of constr
GACODE
- 遗传算法求解优化问题，简明教程加示例- The heredity algorithm solution optimization question, the concise course adds the demonstration
f1
- 多目标优化问题，此例中经遗传算法优化子代个体数目逐步减少，最后稳定在10个染色体个体-Multi-objective optimization problem, in this case, by the genetic algorithm to gradually reduce the number of offspring individuals, and finally stabilized at 10 chromosome individual
PSO
- 粒子群优化算法，主要是函数优化问题。很使用-Particle Swarm Optimization, mainly function optimization problems. Is the use of
gafor01
- 遗传算法求解典型的组合优化问题，复杂背包问题的设计-Genetic Algorithm for typical combinatorial optimization problem, the complexity of the design of knapsack problem
7941925pos
- 粒子群的优化算法，不仅可以方便地解决无约束优化问题，也可以方便的解决有约束的非线性优化问题。-Particle Swarm Optimization algorithm, not only can easily solve the unconstrained optimization problem can also be convenient to solve constrained nonlinear optimization problem.
pso3
- 带交叉因子的改进粒子群优化算法，算法用于示解多维无约束优化问题，收敛性强。-With cross-factor improvement of particle swarm optimization algorithm for multi-dimensional solution that unconstrained optimization problem, convergence is strong.
MOEAD
- 基于微分的多目标优化问题，以子函数的形式写出的-Based on the differential of the multi-objective optimization problem in order to write the form of Functions
SGAC
- 标准遗传算法源码 C语言编程 求解函数优化问题。-Standard genetic algorithm C language programming for Function Optimization.
SA
- 模拟退火实现的连续函数优化问题。仿真效果良好-Simulated annealing to achieve the continuous function optimization problems. Simulation results
SGA
- 一个简单的遗传算法，适用于求解函数优化问题，Visual C++编写。-A simple genetic algorithm for solving function optimization problems, Visual C++ to prepare.
MOPandGA
- 使用强变异演化算法处理高维决策向量情况下的多目标优化问题-Strong variation of the use of evolutionary algorithms to deal with high-dimensional vector in decision-making in case of multi-objective optimization problem
constrainpso
- 一个解决约束优化问题的算法,但是对一个测试函数无法达到全局最优.希望能加以改进并应用。-A solution algorithm for constrained optimization problems, but a test function can not reach the global optimum. Would like to be improved and applied.
TSP
- 模拟退火算法来源于固体退火原理，将固体加温至充分高，再让其徐徐冷却，加温时，固体内部粒子随温升变为无序状，内能增大，而徐徐冷却时粒子渐趋有序，在每个温度都达到平衡态，最后在常温时达到基态，内能减为最小。根据Metropolis准则，粒子在温度T时趋于平衡的概率为e-ΔE/(kT)，其中E为温度T时的内能，ΔE为其改变量，k为Boltzmann常数。用固体退火模拟组合优化问题，将内能E模拟为目标函数值f，温度T演化成控制参数t，即得到解组合优化问题的模拟退火算法：由初始解i和控制参数初值t开始，
MOP
- 用神经网络解决多目标优化问题，其中学习算法用的是用BP学习算法-solve multiple optimization problem by neural network,using BP learning method
PAES-alba.tar
- 用于求解多目标优化问题，多目标进化算法源程序-The code for multi-objective optimization algorithm
DEAgent-algorithm
- 通过DE agent求解各种约束函数优化问题-This source code is discrible the DE agent that is for solving constrained numerical optimization problems.
QEAsolvePackage
- 最近两年比较流行的量子进化算法（QEA），能够求解一般的优化问题。算例是一个典型的背包问题（离散二值问题）。-The more popular the last two years the quantum evolutionary algorithm (QEA), be able to solve the general optimization problems. An example is a typical knapsack problem (discrete binary problem