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[Othertsp

Description: tsp算法源码,简答实现,旅行商问题 可以跑一跑流程(Tsp algorithm source code, easy realization, traveling salesman problem You can run a running process)
Platform: | Size: 2048 | Author: zw_code | Hits:

[AI-NN-PRtsp 2

Description: 使用分布式优化算法的概率思想解决tsp问题,内含一篇相关论文,txt文档复制到matlab中。 一些tsp标准测试数据(结合matlab可直接调用,只需要改掉matlab中调用路径即可) 自己的测试情况。 我算法内在100维以上就运行很慢,而且精度下降,如果有朋友找到解决方法可以联系我,大家学习交流 (比上次的上传完整很多)(using EDA solving tsp)
Platform: | Size: 367616 | Author: 嘟嘟嘟心心 | Hits:

[Mathimatics-Numerical algorithmsTSP Matlab程序

Description: 蚁群算法是当前研究非常火热的一种智能算法,下面的蚁群算法程序专门用于求解TSP问题,此程序由GreenSim团队于2006年初完成,最初公开发表于研学论坛,我们经过仿真检验,发现此程序的优化效率和鲁棒性都非常好。(Ant colony algorithm is an intelligent algorithm very hot current research, the special program of ant colony algorithm for solving the TSP problem, the program completed by the GreenSim team in early 2006, first published in the research forum, we through the simulation test, found the program optimization efficiency and robustness are very good.)
Platform: | Size: 3072 | Author: Victor_Z | Hits:

[source in ebook禁忌算法求解tsp

Description: 利用禁忌搜索算法求解经典TSP问题。假设有一个旅行商人要拜访n个城市,他必须选择所要走的路径,路径的限制是每个城市只能拜访一次,而且最后要回到原来出发的城市。路径的选择目标是要求得的路径路程为所有路径之中的最小值。(Tabu search algorithm for solving classical TSP problems)
Platform: | Size: 14336 | Author: 春天里的 | Hits:

[matlabAA—TSP

Description: 本算法是在MATLAB下,用蚁群算法求解tsp问题(The algorithm is based on MATLAB, ant colony algorithm to solve the TSP problem)
Platform: | Size: 2048 | Author: 亚亚亚 | Hits:

[matlabSA for TSP [www.MatlabSite.com]

Description: sa-tsp algorithm for matlab,this is correct
Platform: | Size: 34816 | Author: arashap | Hits:

[Other基于遗传算法的TSP算法

Description: 一种基于遗传算法的TSP算法,比遗传算法更为合理准确(A TSP algorithm based on genetic algorithm is more reasonable and accurate than genetic algorithm)
Platform: | Size: 6144 | Author: 风沙渡泪无痕 | Hits:

[AI-NN-PRtsp

Description: 使用遗传算法解决tsp问题 人工智能 遗传算法示例(Using genetic algorithm to solve TSP problem)
Platform: | Size: 2416640 | Author: jhhfft | Hits:

[matlab基于模拟退火算法的TSP算法

Description: 基于模拟退火算法的TSP算法的matlab代码示例(TSP algorithm based on simulated annealing algorithm)
Platform: | Size: 5120 | Author: qiu@qiu | Hits:

[AI-NN-PR蚁群算法的优化计算——旅行商问题(TSP)优化

Description: 蚁群算法的优化计算——旅行商问题(TSP)优化(Optimization calculation of ant colony algorithm)
Platform: | Size: 2048 | Author: qiu@qiu | Hits:

[Windows DevelopTSP遗传算法

Description: 遗传算法解决144个城市的TSP问题,并用easyX插件画出路径图。(The genetic algorithm solves the TSP problem in 144 cities and uses the easyX plug-in to draw the path map.)
Platform: | Size: 29848576 | Author: wwwhx | Hits:

[AI-NN-PR基于遗传算法的TSP算法

Description: TSP问题是典型的NP难问题,运用遗传算法解决TSP问题(The TSP problem is a typical np-hard problem, using the genetic algorithm to solve TSP problem)
Platform: | Size: 11264 | Author: wusthc | Hits:

[matlab基于模拟退火算法的TSP算法

Description: 基于模拟退火算法的TSP算法,MATLAB算例实现(MATLAB code for Travelling salesman problem, TSP ,and it is in simulate annealing algorithm)
Platform: | Size: 6144 | Author: corey6 | Hits:

[AI-NN-PR[python]tsp-master

Description: 遗传算法解决TSP问题,python源码,github(Solving TSP problem by genetic algorithm)
Platform: | Size: 6144 | Author: jennie | Hits:

[AlgorithmTabu Search TSP

Description: matlab code for tsp using tabu search
Platform: | Size: 6144 | Author: usgaa | Hits:

[matlabGeneticAlgorithm-TSP-master

Description: tsp solution using genetic algorithm
Platform: | Size: 57344 | Author: eledkawy | Hits:

[matlab蚁群算法的优化计算——旅行商问题(TSP)优化

Description: 路径优化 蚁群算法 tsp问题 优化设计(Path optimization TSP problem of path optimization ant colony algorithm)
Platform: | Size: 2048 | Author: 陈小肥 | Hits:

[matlab蚁群算法求解TSP问题

Description: 将蚁群算法有效应用到TSP问题,并使用Matlab求解(Ant colony algorithm for solving TSP problem)
Platform: | Size: 18432 | Author: c_pcy | Hits:

[matlabtabusearch-TSP

Description: 关于tsp的禁忌搜索方法案例,书上的扣下来的例子(tsp,tabusearch,only for the data)
Platform: | Size: 3072 | Author: LYHM | Hits:

[JSP/JavaTSP遗传算法

Description: 对于TSP问题使用遗传算法的解决方法,其中含有测试数据以及代码数据。(The genetic algorithm is used to solve the TSP problem, which contains the test data and the code data.)
Platform: | Size: 8192 | Author: AlohaHill | Hits:
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