搜索资源列表
SA_GA_PSO
- 模拟退火（SA）、遗传算法（GA）、粒子群优化（PSO）解决旅行商问题（TSP）实验 本文件包括源码，实验说明文档，实验总结PPT Have a happy experiment！-Simulated annealing (SA), genetic algorithms (GA), particle swarm optimization (PSO) to solve the traveling salesman problem (TSP) experiment of this docum
TS-SA
- 禁忌搜索和模拟退火相结合的算法，解决TSP问题。注：31城市。-Tabu search and simulated annealing to a combination of algorithms to solve TSP. Note: The 31 cities.
fireTSP
- 模拟退火解决旅行商（TSP问题）采用康立山等人的算法 能得到最优解，速度可以-Kang Tateyama simulated annealing to solve the traveling salesman (TSP problems) algorithm can get the optimal solution can speed
zhinengTSP
- TSP的matlab神经网络解法，包括遗传算法、粒子群算法 、鱼群算法、模拟退火法程序，程序有注释-The TSP Matlab intelligent solution, including genetic algorithm, particle swarm optimization, fish school algorithm, simulated annealing procedures, procedures comment
test2
- 模拟退火程序解TSP。C++编程用智能优化算法TSP问题，对初学者有一定帮助。-Simulated annealing process solution TSP. C++ programming with intelligent optimization algorithm TSP problem, some help for beginners.
DHUMCM2012-194-B
- 这是一个模拟退火的智能算法，用来解决TSP问题及其衍生问题。-Above using a simulated annealing intelligent algorithms that can solve TSP problem and its derivatives.
program
- TSP问题的遗传、模拟退火、邻域搜索、禁忌搜索算法对比-Genetic TSP problem, simulated annealing, neighborhood search, tabu search algorithm comparison
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
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