搜索资源列表
SGALABbugfix
- 多目标遗传算法程序 to run Demo files, is to run SGALAB_demo_*.m what s new: 1) Multiple-Objective GAs VEGA NSGA NPGA MOGA 2) More TSP mutation and Crossover methods PMX OX CX EAX Boolmatrix 3) More selection methods
tsp.cpp
- 用遗传算法（Genetic algorithm）解决Travel salesperson problem. Crossover类型：one-point和two-point. 选择类型：Tournament和RouletteWheel.
TSP.rar
- 采用visual c解决tsp问题。里面有遗传算法的选择、交叉、变异函数。,Using visual c solve the problem tsp. There are genetic algorithm selection, crossover and mutation functions.
TSP-gene
- 是用遗传算法解决TSP问题，测例包括10个城市和30个城市。使用PMX交叉算子。-Is to use genetic algorithms to solve TSP problems, test cases, including 10 cities and 30 cities. Using the PMX crossover.
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.
TSP
- 遗传算法实现TSP算法，包括选择、交叉等操作-TSP algorithm for genetic algorithm implementation, including selection, crossover, such as operation
genetic
- matlab遗传算法编码 采用基本遗传算法 同时加入刘海交叉法对算法进行改进 解决TSP问题-matlab genetic algorithm coding the basic genetic algorithm using crossover method Liu also added to improve the algorithm to solve TSP problems
Guotao-algorithmic
- 线性非凸多父体杂交算子求解TSP问题。算法将搜索空间看成是一个全空间Ω，种群中的个体可以看作Ω中的一组向量。种群中的若干个向量构成一组基向量，它们可以张成Ω的一个子空间，这些向量随机性组合能相对均匀地搜索这一部分子空间。-Linear non-convex multi-parent crossover operator for solving TSP body problem. Algorithm search space as a full-space Ω, the individual po
tsp
- 该程序解决10个城市的货郎担问题（TSP），主要使用简单的遗传算法实现。该过程中包括：编码、解码，选择，交叉，变异等！-The program to solve the traveling salesman problem of 10 cities (TSP), the use of simple genetic algorithm. The process includes: encoding, decoding, selection, crossover and mutation!
oxcrossover
- crossover in tsp genetic with cx
TSP
- 遗传算法解决tsp问题 问题规模100，杂交，变异，变比，选择方法可选-Genetic algorithm to solve the problem scale of the problem tsp 100, crossover, mutation, transformation ratio, select the method of optional
tsp
- 遗传算法在求解旅行商问题中的应用，采用二进制Gray编码,采用基于轮盘赌法的非线性排名选择, 均匀交叉,变异操作,而且还引入了倒位操作!-Genetic Algorithm for Traveling Salesman Problem, using a binary Gray code, roulette method based on linear ranking selection, uniform crossover and mutation operators, but also in
GA
- matlab 遗传算法求解tsp，有详细的交叉，变异说明，适合初学者-matlab genetic algorithm tsp, detailed crossover, mutation descr iption, suitable for beginners
TSP-GA.zip
- 旅行商问题（TSP）是一个经典的优化组合问题，本个案列采用遗传算法来求解TSP问题，进行了选择、交叉、变异算子的设计，并通过MATLAB对算法进行了实现，附有详细的说明和代码。,The traveling salesman problem (TSP) is a classic combination optimization problem, in this case the column using a genetic algorithm to solve TSP problem select
tsp
- 本程序为神经网络解决TSP问题 数据有100城市 200城市和500城市，采用VC++编程 程序中已经设置成最佳参数 交叉驴0.6 变异率0.01 @ 迭代500 代。效果不错-The procedures for the neural network to solve the TSP data of 100 cities 200 cities and 500 cities, using VC++ programming procedure has been set to the optim
tsp-GA
- 遗传算法解决TSP问题，词程序为30个城市的TSP问题，其中交叉和变异函数有点问题，在结果中可能无法遍历30个城市-Genetic algorithm to solve TSP, the word program is 30 cities TSP problem where a problem with the crossover and mutation function, the result may not traverse 30 cities
tsp
- 遗传算法（Genetic Algorithm）是模拟达尔文生物进化论的自然选择和遗传学机理的生物进化过程的计算模型，是一种通过模拟自然进化过程搜索最优解的方法 遗传算法的基本运算过程如下： a)初始化：设置进化代数计数器t=0，设置最大进化代数T，随机生成M个个体作为初始群体P(0)。 b)个体评价：计算群体P(t)中各个个体的适应度。 c)选择运算:将选择算子作用于群体。选择的目的是把优化的个体直接遗传到下一代或通过配对交叉产生新的个体再遗传到下一代。选择操作是建立在群体中个体
TSP
- 根据混合粒子群算法原理，在MATLAB中编程实现基于粒子群算法的TSP搜索算法，给出了适应度函数，粒子初始化，交叉操作，变异操作，最后给出了仿真结果。有图可以看出，混合粒子群算法能够较快找到连接各个城市的最优路径，谢谢，希望能够给大家带来帮助。-According to the principle of hybrid particle swarm algorithm, programmed in MATLAB Based on Particle Swarm TSP search algorith
TSP-PSO
- 混合粒子群算法摒弃了传统粒子群算法中的通过跟踪极值来更新粒子位置的方法，而是引入了遗传算法中的交叉和变异操作，通过粒子同个体极值和群体极值的交叉以及粒子自身变异的方式来搜索最优解。(Hybrid particle swarm algorithm instead of the traditional particle swarm algorithm in the method to update the position of the particle by tracking the maximu
code
- 基于蚁群算法的 TSP 求解，分别采用蚁群算法和蚁群算法-粒子群混合算法进行优化求解，使用不同的交叉和变异适应度函数更新粒子，从而实现 TSP问题的优化求解，更加逼近实际问题。(Based on the TSP solution of ant colony algorithm, ant colony algorithm and hybrid algorithm of ant colony algorithm particle swarm optimization are used to solv