Description: 用matlab实现的利用模拟退火算法(SA)解决旅行商问题(TSP).-Matlab achieved with the use of simulated annealing algorithm (SA) to solve traveling salesman problem (TSP). Platform: |
Size: 477184 |
Author:黄卢荃 |
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Description: 使用模拟退火算法求解TSP（旅行商）问题的JAVA源程序-The use of simulated annealing algorithm for solving TSP (traveling salesman) problem with JAVA source Platform: |
Size: 3072 |
Author:ann |
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Description: 模拟退火算法解旅行商问题，读入的文件描述城市的位置，采用康立山等人的方法，能以较大的概率接触最优解-Simulated annealing algorithm traveling salesman problem, read the document describes the city s location, KANG Li-shan, who adopted the method, to a greater probability of exposure to the optimal solution Platform: |
Size: 1024 |
Author:赵九鑫 |
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Description: 旅行商（TSP）问题一直以来都是一个NP难问题，旅行商问题（TSP问题）就是一销售商从n个城市中的某一城市出发，不重复地走完其余n-1个城市并回到原出发点，在所有可能的路径中求出路径长度最短的一条。本次软件设计是利用模拟退火算法解决TSP问题，通过该软件设计，对模拟退火算法和旅行商问题有个初步的认识。-Traveling Salesman (TSP) problem has always been a NP hard problem, traveling salesman problem (TSP problem) is a vendor from the n cities in a city of departure, not repeated through the remaining n-1 cities and back to to the original starting point, in all possible path to derive a shortest path length. The software design is the use of simulated annealing algorithm to solve TSP problems, the adoption of the software design, on the simulated annealing algorithm and the traveling salesman problem to have a preliminary understanding. Platform: |
Size: 1024 |
Author:周薇 |
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Description: 用模拟退火算法解决旅行商类优化问题，有算法和例子，很好用。-Using simulated annealing algorithm to solve traveling salesman optimization problem category, there are algorithms and examples of good use. Platform: |
Size: 2048 |
Author:gjj |
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Description: 用模拟退火算法对求解旅行商组合优化问题作了一定的研究，提出了多种不同的随机抽样方式，并对其进行了分析计算并以代码实现。
-This paper studied the optimizing of the traveling salesman problem with the Simulated Annealing(SA)．
Different random sampling forms were proposed and analyzed．
Platform: |
Size: 7827456 |
Author:裴 |
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Description: 人工智能中，用模拟退火方法解决旅行商问题,采用C++实现-Artificial intelligence, the use of simulated annealing to solve traveling salesman problem, using C++ implementation Platform: |
Size: 10240 |
Author:张宁 |
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Description: 使用模拟退火算法求解10城市和20城市的旅行商问题，城市数目和城市之间的距离保存在txt文件中，程序读入数据后求解最优路径-The use of simulated annealing algorithm 10 cities and 20 cities in the traveling salesman problem, the number of cities and the distance between the cities stored in the txt file, the program read the data to solve the optimal path Platform: |
Size: 614400 |
Author:郑益夫 |
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Description: 首先介绍模拟退火算法，然后编写伪程序，结合Visual C++开发工具求解著名的旅行商问题TSP-Simulated annealing algorithm first introduced, and then the preparation of pseudo-process, combined with Visual C++ development tools for solving the famous Traveling Salesman Problem TSP Platform: |
Size: 927744 |
Author:liuzhiyong |
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Description: 该程序是模拟退火算法应用中旅行商问题的c++程序-The procedure is the application of simulated annealing algorithm for the traveling salesman problem c++ program Platform: |
Size: 641024 |
Author:586 |
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Description: 模拟退火算法解决旅行商问题-希望对大家有用-Simulated annealing algorithm to solve traveling salesman problem- I hope useful for all of us Platform: |
Size: 1024 |
Author:ww |
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Description: 旅行商问题的模拟退火算法实现 采用VHDL仿真，软件java来varificatio。本例中采用16个城市-Traveling Salesman Problem Algorithm of Simulated Annealing using VHDL simulation, software, java to varificatio. In this case the use of 16 cities Platform: |
Size: 19693568 |
Author:Zoe |
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Description: 模拟退火和对称
*欧几里德旅行商问题。
*
*为基础的解决办法的本地搜索启发式
*非过境道路和近邻
-/*
* Simulated annealing and the Symetric
* Euclidian Traveling Salesman Problem.
*
* Solution based on local search heuristics for
* non-crossing paths and nearest neighbors
*
* Storage Requirements: n^2+4n ints
*
* Problem: given the coordinates of n cities in the plane, find a
* permutation pi_1, pi_2, ..., pi_n of 1, 2, ..., n that minimizes
* sum for 1<=i<n D(pi_i,pi_i+1), where D(i,j) is the euclidian
* distance between cities i and j
*
* Note: with n cities, there is (n-1)!/2 possible tours.
* factorial(10)=3628800 factorial(50)=3E+64 factorial(150)=5.7E+262
* If we could check one tour per clock cycle on a 100 MHZ computer, we
* would still need to wait approximately 10^236 times the age of the
* universe to explore all tours for 150 cities.
*
* gcc-O4-o tsp tsp.c-lm tsp | ghostview-
*
* Usage: tsp [-v] [n=dd] [s=dd] [filename]
* -v : verbose
* n= : nb of cities (cities generated randomly on E^2 Platform: |
Size: 86016 |
Author:孙博 |
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Description: 用模拟退火的算法解决中国旅行商的问题，结果画出图形直观明了！-Using simulated annealing algorithm to solve traveling salesman problem of China, resulting in intuitive and clear graphics to draw! Platform: |
Size: 19456 |
Author:王大伟 |
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Search - salesman annealing