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模拟退火算法解决函数优化问题，智能信息处理课程的实验，感兴趣的可以下载-Simulated annealing algorithm to solve function optimization problems, the course of the experiment of Intelligent Information Processing, interested can download and see
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通过例子讲解模拟退火法的优化原理和方法，浅显易懂！-The global minimum of function can be obtained by the simulated annealing algritm.
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自己编写的模拟退火粒子群算法，里面含有测试函数，比较简单，适合初学者。-I have written simulated annealing particle swarm algorithm, which contains a test function is relatively simple, suitable for beginners.
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本资源是Mgasa算法解决TSP问题的Matlab代码，资源中包括mgasa_main(Mgasa算法解决TSP问题代码)，mgasa_fitness(适应度求取函数代码)，mgasa_annealing(Mgasa算法中模拟退火代码)，mgasa_select(遗传算法中选择函数代码)，mgasa_crossover(遗传算法中染色体交叉互换函数代码)，mgasa_mutation(遗传算法中基因突变函数代码)，mgasa_change(Mgasa算法中选择过程代码)。同时代码中有Locati
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基于混沌的模拟退火算法，数学方法是部分子空间法，自写曲率计算函数 。- Chaos-based simulated annealing algorithm, Mathematics is part of the subspace, Since writing the curvature calculation function.
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用C++实现了模拟退火算法求多元函数极值,可以避免陷入局部最优解-By c++ implementation of a simulated annealing algorithm for multivariate function extreme value, can avoid falling into local optimal solution
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介绍模拟退火算法的功能和matlab程序(The function and matlab program of simulated annealing algorithm are introduced)
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