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General simulated annealing algorithm-anneal Minimizes a function with the method of simulated annealing (Kirkpatrick et al., 1983)
ANNEAL takes three input parameters, in this order:
LOSS is a function handle (anonymous function or
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模拟退火算法解决TSP问题，用固体退火模拟组合优化问题，将内能E模拟为目标函数值f，温度T演化成控制参数t，即得到解组合优化问题的模拟退火算法：由初始解i和控制参数初值t开始，对当前解重复“产生新解→计算目标函数差→接受或舍弃”的迭代，并逐步衰减t值，算法终止时的当前解即为所得近似最优解-Simulated annealing algorithm to solve the TSP problem, combined with solid-annealing simulation optimiza
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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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通过MATLAB编程，实现模拟退火算法的功能，一次实现TSP问题。-Through MATLAB programming, to achieve the function of simulated annealing algorithm, a TSP problem.
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By c + + implementation of a simulated annealing algorithm for multivariate function extreme value, can avoid falling into local optimal solution-By c++ implementation of a simulated annealing algorithm for multivariate function extreme value, can av
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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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八皇后的经典算法，是一个古老而著名的问题，是回溯算法的典型案例。任意两个皇后都不能处于同一行、同一列或同一斜线上，问有多少种摆法(Simulated annealing algorithm, the function of the most value)
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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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