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遗传算法解决TSP问题
- 大家好!这是一个由VC编写的遗传算法解决TSP问题的源代码，希望能初学者有所帮助!-everyone! This is a VC prepared by the Genetic Algorithm for the Traveling Salesman Problem source code, hope to help beginners!
acs_TSP
- 蚁群算法VB源代码,解决TSP问题的程序,有多种TSP问题解答!-Ant Algorithm VB source code to solve the TSP process, a number of TSP answer!
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- 设计一个求解图着色的问题的算法，（不可以用贪心算法）及用贪心算法设计一个TSP问题-Design a plan for solving the problem coloring algorithm, (can not use greedy algorithm) and greedy algorithm design using a TSP problem
ANTtsp
- 蚁群算法求解TSP问题， 蚁群算法求解TSP问题-Ant colony algorithm for TSP, the ant colony algorithm for TSP, the ant colony algorithm for TSP
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- 使用蚁群算法解决TSP问题得出最佳的城市循环路径-An Approach for TSP problem based on Ant Colony Algorithms
a
- 用粒子群算法解决tsp问题，可以引用数据包-With particle swarm algorithm to solve tsp problem
ga_tsp
- 遗传算法小程序,关于解决TSP问题的遗传算法,仅供参考-GA small program on the settlement of the TSP Genetic Algorithm for reference purposes only and interact more
lvxingshang
- JAVA实现旅行商问题，有简单的可视化界面 有N个城市，要求从其中某个问题出发，唯一遍历所有城市，再回到出发的城市，求最短的路线。使用模拟退火算法可以比较快的求出TSP的一条近似最优路径。-JAVA traveling salesman problem, a simple visual interface There are N cities, which to ask a question, the only way to traverse all cities, and then
模拟退火tsp问题
- 这篇matlab程序应用模拟退火算法解决tsp问题(This matlab program uses simulated annealing algorithm to solve the TSP problem)
s4_7
- 基于SGA算法解决TSP问题，使用excel将城市的坐标导入到matlab(Based on the SGA algorithm to solve the TSP problem, the use of Excel coordinates the city into the MATLAB)
TS-TSP
- 用TS算法解决推销商最短路径问题，数据是中国的各个省会和直辖市(Salesman to solve the shortest path problem with TS algorithm, the data is Chinese all provincial capitals and municipalities directly under the central government)
ufhry
- 本资源包括基于模拟退火算法解决TSP问题的相关代码以及TSP的城市数据()
Python-Ant-Colony-TSP-Solver-master
- 用蚁群算法解决tsp问题的python代码实现(tsp Ant System python code)
7943515
- 资源包含遗传算法解决TSP问题=的相关代码以及TSP相关的城市数据()
tsp
- matlab源代码用模拟退火算法求解TSP问题(we use SA to solve TSP problem, This is the matlab code.)
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- TSP是典型的NP完全问题，即其最坏情况下的时间复杂度随着问题规模的增大按指数方式增长，遗传算法可进行有效求解(TSP is a typical NP-complete problem, that is, the time complexity in the worst case increases exponentially as the scale of the problem increases, and the genetic algorithm can be effectively s