搜索资源列表
simulated-annealing
- 清华大学本科生智能优化课程报告,用模拟退火算法和遗传算法解决TSP问题,含核心代码和注释-Tsinghua University undergraduate course reports intelligent optimization, simulated annealing algorithm and genetic algorithm to solve TSP problem, including the core code and comments
SA_TSPproblem
- TSP问题(货郎担问题,旅行商问题)的模拟退火算法通用malab源程序-TSP problem (traveling salesman problem, traveling salesman problem) simulated annealing algorithm malab common source
SA
- 基于模拟退火算法的TSP问题解算方法和二维路径规划-Based on simulated annealing algorithm for TSP solution method and two-dimensional path planning
SA
- 模拟退火算法解决TSP问题源程序(C++)-SA for TSP
SA_tsp
- 使用模拟退火算法解决tsp问题,运行得到最优解的概率在80 以上-solve tsp problem with Simulated Annealing algorithm
matlab
- 很全的智能算法,包括粒子群算法、模拟退火算法、遗传算法、TSP问题求解、蚁群算法、人工神经网络算法以及相关结合算法-A full of intelligent algorithm, including the particle swarm algorithm, simulated annealing algorithm, genetic algorithm, the TSP problem, ant colony algorithm, and the combination of artific
SSA_TSP
- 基于模拟退火发求解TSP问题,其中包含一个主程序和四个子程序,可修改参数-Solving TSP problem based on SSA
simulated-annealing(SA)
- 模拟退火方法解决TSP问题,代码用MATLAB实现,可直接运行,可自行修改初始城市数据-Simulated annealing algorithm to solve TSP problem, the code using MATLAB to achieve, can be run directly, you can modify the initial data on their own city
aiwa
- 求解tsp问题的MATLAB程序,模拟退火算法源程序-MATLAB problem solving procedures tsp
GA100
- 利用模拟退火发求解TSP问题。Location.dat存储了每个城市的坐标-Simulating Anealing Method for TSP
ACO3
- 融合蚁群算法和模拟退火算法的C++程序,解决TSP-Fusion ant colony algorithm and simulated annealing algorithm C++ program to solve TSP
MNTH_TSP
- 1. 本程序使用模拟退火算法解决TSP问题 a) 初始温度确定方法 选取任意状态为初始状态。以1为起始温度,不断升温,直到模拟所得接受概率大于90 ; b) 温度下降 温度下降系数为 0.95; c) 每一温度迭代 选取固定迭代次数 100 * n; d) 终止条件 温度下降次数到达 800,或某一温度下解不发生改变; 2. 本机运行及编译环境 win7 旗舰版 SP1 MINGW g++ 4.8.1 -Simu
mgasa
- 本资源是Mgasa算法解决TSP问题的Matlab代码,资源中包括mgasa_main(Mgasa算法解决TSP问题代码),mgasa_fitness(适应度求取函数代码),mgasa_annealing(Mgasa算法中模拟退火代码),mgasa_select(遗传算法中选择函数代码),mgasa_crossover(遗传算法中染色体交叉互换函数代码),mgasa_mutation(遗传算法中基因突变函数代码),mgasa_change(Mgasa算法中选择过程代码)。同时代码中有Locati
MatLab-Script
- 基于启发式(Heuristic)的人工智能算法解决旅行商问题(Traveling Salesman Problem)。关键词:模拟退火,遗传算法。工作环境:matlab-An artificial intelligence algorithm based on heuristic to solve Traveling Salesman Problem(TSP). Key words: Simulated Annealing, Genetic Algorithm. Working environm
Simulated-Annealing-matlab
- 利用模拟退火算法寻找我国31个省会城市(不含港澳台)的TSP最短路径.输出最短路径顺序及其长度,以及模拟退火算法迭代过程中的最短路径长度进化曲线-Simulated annealing algorithm to find China' s 31 provincial capital cities (excluding Hong Kong, Macao and Taiwan) of TSP shortest path shortest path output sequence and len
SA_TSP
- tsp问题的模拟退火算法求解,在matlab环境下运行- 检测到:中文 » 英语 Simulated annealing algorithm to solve TSP problems, in the matlab environment
simulated-annealing
- 19基于模拟退火算法的TSP算法 有源代码及图片-simulated annealing
SAA
- 模拟退火智能算法解决经典TSP问题,方便修改,注释方便理解-SAA only classical algorithm to solve TSP problem, easy to modify, easy to understand comments
monituihuo
- 模拟退火算法的源代码,可有效解决旅行商问题(TSP)。-Simulated annealing algorithm source code, which can effectively solve the traveling salesman problem (TSP).
SA_TSP
- 用模拟退火算法求解TSP问题,matlab源码,绝对可运行。-Solving traveling salesman problem with simulated annealing algorithm,matlab code.