搜索资源列表
TS-TSP.rar
- 使用禁忌搜索算法求解TSP（旅行商问题）的JAVA源程序,The use of tabu search algorithm for solving TSP (Traveling Salesman Problem) the JAVA source code
tsp.rar
- 这是一个很好用的求解TSP问题的粒子群算法，很适合初学者。,This is a very good solution of TSP used in the particle swarm optimization problems, it is suitable for beginners.
design.rar
- 回溯法，动态规划法，遗传算法求解 tsp问题（课程设计报告）,Backtracking, dynamic programming method, genetic algorithm tsp issues (curriculum design report)
TSP-PSO.rar
- 用混合粒子群算法求解TSP问题，自带GUI界面，共有９中算法，可解决各种TSP问题，效果不错。,Using hybrid particle swarm algorithm to solve TSP problems, bring their own GUI interface, a total of 9 in the algorithm, to resolve the various TSP problems, good results.
PSO-TSP.rar
- 本程序是一个用POS来求解NP难问题，比图TSP问题，实际仿真效果证明改算法合理,This procedure is a POS to use NP hard problem to solve than the TSP problem graph, the actual simulation results prove that a reasonable change algorithm
TSP-MST.rar
- 最小生成树的思想应用于TSP问题的求解，贪心算法的实际应用。,Minimum Spanning Tree thinking applied to TSP problem solving, the practical application of greedy algorithm.
蚁群算法求解TSP问题的matlab程序
- %蚁群算法求解TSP问题的matlab程序 clear all close all clc %初始化蚁群 m=31;%蚁群中蚂蚁的数量，当m接近或等于城市个数n时，本算法可以在最少的迭代次数内找到最优解 C=[1304 2312;3639 1315;4177 2244;3712 1399;3488 1535;3326 1556;3238 1229;4196 1004; 4312 790;4386 570;3007 1970;2562 1756;2788 1491;2381 1
GA_TSP
- 利用遗传算法求解TSP问题。TSP问题描述如下：给定一组n个城市和他们两两之间地直达距离，寻找一条闭合的旅程，使得每个城市刚好经过一次而且总的旅行距离最短。 -The use of genetic algorithm to solve TSP problem. TSP problem described as follows: given a set of n cities and they are between 22 to direct the distance of the journey
TSP
- 遗传算法求解经典的旅行商(TSP)问题。图形化界面，可以选择大/中/小地图文件，并演示进化的过程。中/小地图在默认代数下一般都可以找到最优解。-Genetic Algorithm for the classic TSP problem. Graphical interface, you can choose large/medium/small map files, and demonstrates evolutionary process. Medium/small maps in the d
particle_swarm_optimization-Solve-the-TSP-problem.
- 基于粒子群优化算法（PSO）的50个城市TSP问题的求解，可推广至类似NP-hard问题。-Based on Particle Swarm Optimization (PSO) of the 50 cities TSP problem solving can be extended to a similar NP-hard problem.
tsp
- 用动态规划法求解TSP问题的C++源码 在Linux中用g++编译通过-Using dynamic programming method for solving TSP problems C++ Source code in Linux using g++ Compiled through
tsp
- hopfield神经网络求解TSP问题，改程序设置了10个城市的随机位置，进而解决城市间最短路径问题。-hopfield neural network to solve TSP problem, the procedures set up to 10 cities random location, then the shortest path between cities to solve problem.
generic_tsp
- 用遗传算法求解TSP问题，种子数100，遗传概率和交叉概率可以在源程序中修改。-Genetic Algorithm with TSP problem, a few hundred seeds, genetic probability and crossover probability can modify the source program.
tspsa
- 针对基于遗传算法的TSP 问题求解, 尝试了多种遗传操作, 分析了这些操作在遗传算法中的作用, 讨论了基因片段保序在利用遗传算法求解TSP 问题中的重要性.-Based on Genetic Algorithm for TSP Problem Solving, try a variety of genetic manipulation, analysis of these operations at the role of genetic algorithm discussed Orderin
Grefenstette
- Grefenstette编码法的MATLAB实现 本文在MATLAB环境下编程实现针对TSP问题的Grefenstette编码法,并将其同基本遗传算法相结合,仿真求解一个 15点的TSP问题-Grefenstette coding method to achieve this paper, the MATLAB environment in MATLAB programming for the TSP problem Grefenstette coding method and geneti
TSP
- 免疫算法和模拟退火算法求解TSP问题的研究。本文提出了一种新的免疫模拟退火法，并将其应用于求解典型的NP问题—TSP问题-Immune algorithm and simulated annealing algorithm for solving TSP problems. In this paper, a new immune simulated annealing algorithm, and applies it to solve the issue of a typical NP pro
TSP
- 免疫算法和模拟退火算法求解TSP问题的研究 本文提出了一种新的免疫模拟退火算法，并将其应用于求解典型的NP问题—TSP问题 -Immune algorithm and simulated annealing algorithm for solving TSP problems is proposed in this paper a new immune simulated annealing algorithm, and applies it to solve the issue of
tsp
- 该程序是蚁群算法和遗传算法的混合算法的C语言程序在求解TSP问题时的应用，可以进行扩展到其他问题的两种算法应用-The program is ant colony algorithm and genetic algorithm hybrid algorithm in the C language program to solve the issue of the application of TSP, can be extended to other applications of the tw
tsp
- 遗传算法求解tsp问题的matlab代码-Genetic algorithm matlab code issues tsp
tabu_search-Solve-the-TSP-problem
- 基于禁忌搜索算法的50个城市TSP问题的求解，可推广至类似NP-hard问题。-Tabu search algorithm based on the 50 cities TSP problem solving can be extended to a similar NP-hard problem.