搜索资源列表
CTSP_SA
- 简单明晰的运用模拟退火算法解决中国旅行商问题的Matlab程序。动态绘制图像并输出结果和访问路径序列。-Sovling Chinese TSP using SA with Matlab. Exporting result & path & picture.
ZEKIN-DOMACI
- matlab model sa vezbi trala ta ta joj
samping
- sa(t)的临界采样、过采样、欠采样的matlab实现与重构-sa (t) critical sampling, over-sampling, under-sampling matlab and Reconstruction
VRP-1
- this code solves vehicle routing problem using simulated annealing algorithm in matlab. in this code , we create different models and then evaluate them using SA algorithm. one of the advantage of this code , is that code is splitting diff
sso_simple
- simplified swarm optimization的matlab版本,可以節省寫程式的時間。本程演算法已驗證可以在某些問題上找到比pso、ga、sa、ts、aco等演算法更好的解。-simplified swarm optimization in matlab version, you can write a program to save time. The scheduling algorithm has been verified can find better than pso,
Algorithms
- matlab源码:K-means算法,粒子群算法PSO,模拟退火算法SA-The matlab source code: K- means algorithm, particle swarm optimization (PSO, simulated annealing algorithm SA
SAforVRP
- Matlab编写的,利用 SA算法解决VRP问题-Matlab prepared using the SA algorithm to solve the VRP
sat
- Sa(t)的临界采样及信号重构 连续时间的冲激序列采样后还原。-Impulse sequence and matlab
anneal
- this is General SA code for matlab maybe can helpful for all
Simulated-Annealing
- SA with schwefel matlab code
VRP_algorithm
- 5个求解车辆路径问题(VRP)的MATLAB算法源程序和相应数据(数据也在m文件里),包括三种遗传算法,SA算法和禁忌搜索算法的m文件-5 solving vehicle routing problem (VRP) MATLAB algorithm source and the corresponding data (data is also in the m file), including three kinds of genetic algorithm, SA algorithm and
SA_TSP
- 使用模拟退火算法解决旅行商问题,在matlab里面实现-use SA algorithm to solve traveling salesman problem
tsp
- matlab源代码用模拟退火算法求解TSP问题(we use SA to solve TSP problem, This is the matlab code.)
神经网络入门13课源码
- 神经网络入门13课源码 第一课 MATLAB入门基础 第二课 MATLAB进阶与提高 第三课 BP神经网络 第四课 RBF、GRNN和PNN神经网络 第五课 竞争神经网络与SOM神经网络 第六课 支持向量机( Support Vector Machine, SVM ) 第七课 极限学习机( Extreme Learning Machine, ELM ) 第八课 决策树与随机森林 第九课 遗传算法( Genetic Algorithm, GA ) 第十课 粒子群优化( Part
chapter7
- 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
5个求解车辆路径问题
- 5个求解车辆路径问题(VRP)的MATLAB算法源程序和相应数据(数据也在m文件里),包括三种遗传算法,SA算法和禁忌搜索算法的m文件