搜索资源列表
tspant_CSharp
- 蚁群算法(ant colony optimization, ACO),又称蚂蚁算法,tsp用C#编程-Ant colony algorithm (ant colony optimization, ACO), also known as the ant algorithm, tsp Programming with C#
Ant-colony-algorithm
- 主要用蚁群算法用matlab实现,解决城市之间最短路径问题-Ant colony algorithm to achieve the TSP
图论算法的matlab程序实现
- 本资源涵盖了几乎所有matlab图论领域里的算法代码,最短路问题、TSP、最大流、深度优先搜索、广度优先、蚁群算法等等,可为功能强大。
ACO_AIA_PSO
- 综合粒子群和蚁群算法,再利用免疫算法中交叉变异算子;形成ACO-AIA-PSO混合算法,求解TSP问题-Integrated particle swarm and ant colony algorithm, and then use the crossover operator and mutation operator of immune algorithm the formation of ACO-AIA-PSO hybrid algorithm, for solving the TSP
ACO---Code-
- 蚁群算法和遗传算法的源码,性能比较,有搜索过程的界面显示,MFC框架-Ant colony optimization and Genetic Algorithm for TSP,developed in MFC
City
- 一个用C++写的基本的蚁群ACO算法,用于解决旅行商TSP问题-ACO TSP
sas
- 一段用C++写的排序蚁群算法,用于求解旅行商TSP问题-ACO TSP
ant-aco
- 改进的蚁群算法,并不是单纯的解决TSP问题,可以实现源节点到目的节点的协作通信。-Improved ant colony algorithm to solve the TSP is not a simple problem, you can achieve collaborative communication source node to the destination node.
ACS-31TSP
- 自己改进的蚁群算法求解31城市tsp问题的程序-Own improved ant colony algorithm program 31 cities tsp problem
ant_TSP
- 蚁群算法解决TSP问题,采用C++编写,简单易懂,-ANT algorithm
ACATSP
- 蚁群算法用于解决TSP问题,算法收敛性好,能够得到满意解-Ant colony algorithm for solving TSP problem, convergence is good, can be satisfied with the solution
ant11
- TSP解答。是智能优化算法的重要问题,采用了蚁群优化算法。-TSP solution. It is an important problem of intelligent optimization algorithm, the ant colony optimization algorithm
ACS
- 蚁群算法求解TSP 假设条件: 1、非对称桥上的信息量与过去一个时间段内经过该桥的蚂蚁数目成正比; 2、某一时刻蚂蚁按照桥上残留的信息量多少来选择其中某座桥 3、经过该桥的蚂蚁数目越多则桥上的残留信息量就越大 -ACS for TSP
AC_TSP
- 蚁群算法求解TSP问题的Matlab源代码-Ant colony algorithm for TSP problem Matlab source code
ACA
- matlab实现的蚁群算法(ACA)例程,解决TSP旅行商问题,可以在图中进行动态显示-ant colony algorithm matlab realized (ACA) routines to solve the traveling salesman problem TSP, can be dynamically shown in the figure
ycsf
- matlab 遗传算法GA,粒子群算法PSO,蚁群算法AS 前段时间上智能计算方法实验课上,自己做的程序。帖到这里,希望有人能改进它们,交流经验这样更有价值。 遗传算法解决最小生成树问题,PURFER编码。 粒子群算法做无约束最优化问题。 蚁群算法解决TSP问题。 -matlab genetic algorithm GA, particle swarm optimization PSO, some time ago on the ant colony algorithm intelligent
ACO---pso-MTSP-
- 基于蚁群—粒子群的TSP求解,可以解决蚁群算法陷入局部最优解的问题,更好求出TSP问题-Based on ACO- pso MTSP solving the problem can be solved ant colony algorithm into local optimal solution, obtaining better TSP problem
51
- 蚁群算法,使用matlab语言,解决TSP问题,此例解决的51个城市的TSP问题-Colony algorithm, using matlab language, solve TSP, in this case solved 51 cities TSP problem
TSP_ACO_MMAS
- 用蚁群算法求解旅行商问题,城市数量为50,迭代500次-to solve tsp with ant
ANT_TSP
- 基本蚁群算法,介绍了种群产生,信息素的更新以及启发式信息的定义。测试例子为TSP问题。-Ant colony algorithm, introduced populations produce, update, and define the heuristic information pheromone. Test case for the TSP problem.