搜索资源列表
模拟退火
- 本程序用模拟退火算法实现了旅行商问题（tsp问题）-the procedures used simulated annealing algorithm to achieve the traveling salesman problem (tsp)
基于模拟退火算法的halilton路径算法
- 哈密尔顿路径问题是个经典的NP问题，本程序 采用模拟退火技术实现了该问题-Hamilton routing problem is a classic NP problem, the procedures used simulated annealing technology of the problem
遗传算法和模拟退火算法相结合的并行实现
- 遗传算法和模拟退火算法相结合的并行实现-genetic algorithms and simulated annealing algorithm combining the parallel implementation
tsp的模拟退火算法
- 神经网络中的tsp的模拟退火算法的matlab实现-neural network tsp of the simulated annealing algorithm to achieve the Matlab
模拟退火算法实现旅行商算法
- 采用的是康力山等人确定的实验参数。 对于n个城市的旅行商问题，其参数如下： 初始温度：t0=280, 每一个温度下采用固定的迭代次数L=100n, 温度的衰减系数alpha=0.92 算法停止的准则是当相邻两个温度得到的解变化很小时算法停止。-used the Stanozolol Hill were determined by the experimental parameters. N cities for the traveling salesman problem, the para
SA_TSP_Rev1
- 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).
SA
- 改进模拟退火算法，应用并实现，希望对大家有所帮助。-Improved simulated annealing algorithm, the application and to achieve, I hope all of you to help.
monituihuo
- 对模拟退火算法的实现，代码写的比较详细。初学此算法的朋友可以参考下。-Simulated annealing algorithm for the realization of the code written in more detail. Learning algorithm can refer to the next friend.
TspSA
- 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．
ModernAlgorithmCosole
- 多进程实现现代优化算法包括采用SSS的局部搜索、禁忌搜索算法和模拟退火算法的控制台-a console platform for modern optimization algorithm such as sss based local search taboo search and simulated annealing algorithm and so on
Simulated
- 人工神经网络中经典模拟退火算法的实现，在VC下可运行-Simulated annealing algorithm
Simulated_annealing_matlab
- 模拟退火算法实验，使用MATLAB实现。-The simulated annealing algorithm, using MATLAB experiment.
simulated-annealing-algorithm
- 用模拟退火算法实现求函数极值问题，c++原码-Simulated annealing algorithm demand function, extremal problem, c++ source
TSP
- 用模拟退火算法和遗传算法实现TSP旅行商问题，并可以用Matlab对结果进行图形显示分析，非常实用于初学者-Using simulated annealing algorithm and genetic algorithm traveling salesman problem TSP, and the results can be used Matlab graphics analysis, very useful for beginners
watchanddoaboutmonituihuo
- 模拟退火算法的非常详细的介绍，模拟退火的基本理论、算法实现、实例-profile about monituihuo.basic knowlege/examples/realization
TSP-based-on-improved-pso
- 基于对粒子群优化算法原理的分析，实现了一种基于TSP的改进的粒子群优化算法：求解TSP的混合粒子群算法，结合遗传算法、蚁群算法和模拟退火算法的思想来解决TSP问题。-Particle swarm optimization based on the principle of the analysis, implemented based on TSP, improved particle swarm optimization algorithm: solving the TSP hybrid pa
模拟退火算法
- 模拟退火算法是一种演化算法，在很多地方都有应用，这是一个C语言实现的模拟退火程序。(A simulated annealing program wiitten by C.)
模拟退火算法tsp
- 用matlab实现模拟退火实现tsp问题。(Using MATLAB to achieve simulated annealing to achieve TSP problem.)
MN
- 模拟退火算法的实现代码，很好的例子，有助于学习算法。(Simulated annealing algorithm implementation code, a very good example of learning algorithm.)
粒子群算法
- 粒子群算法，也称粒子群优化算法或鸟群觅食算法(Particle Swarm Optimization)，缩写为 PSO， 是近年来由J. Kennedy和R. C. Eberhart等 开发的一种新的进化算法(Evolutionary Algorithm - EA)。PSO 算法属于进化算法的一种，和模拟退火算法相似，它也是从随机解出发，通过迭代寻找最优解，它也是通过适应度来评价解的品质，但它比遗传算法规则更为简单，它没有遗传算法的"交叉"(Crossover) 和"