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一系列好用的用户友好的启发式优化算法，包括非自适应算法，基于模拟退火算法的种群算法，基本遗传算法，差分进化算法以及粒子群优化算法。此外，也包括神圣算法，它利用了所有这些优化算子，虽然有时交换种群之间的不同算法。-A nice set of user-friendly heuristic optimizers. Included are a non-adaptive, population based Simulated Annealing algorithm, a basic Genetic A
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Genetic Algorithm optimization using bi-partite graph
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遗传算法
求下列函数的最大值
obj(x)=x.*(10-x).*sin(2*pi*x), x\in[0,10].-Optimization problem by genetic algorithm of a function
obj(x)=x.*(10-x).*sin(2*pi*x), x\in[0,10].
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本程序用来实现对非线性函数求解优化程序的主要算法采用遗传算法实现-This procedure is used to achieve non-linear functions to solve optimization procedure using genetic algorithm main algorithms
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有关多目标优化问题的遗传算法的基本理论方法的硕士论文，相关领域的大家可以参考一下-Multi-objective optimization problems related to genetic algorithms basic theories and methods of the master' s thesis and related fields that we can reference
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给予免疫遗传算法的QOS路由选择问题，给予免疫遗传算法的多目标优化问题-Immune genetic algorithm for QOS routing problem, the immune genetic algorithm for multi-objective optimization problem
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基于免疫遗传算法的QOS路由选择问题
给予免疫遗传算法的多目标优化问题
-Immune genetic algorithm based QOS routing problems provide the immune genetic algorithm for multi objective optimization problem
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人工智能（模糊在自动控制的应用）电动机控制中的简单遗传算法PID参数优化-Artificial intelligence (fuzzy in Automatic Control) motor control in the simple genetic algorithm optimization of PID parameters
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基于群体搜索的遗传算法求解多目标优化问题具有独特的优势,多目标优化算法已有的研究大多为
算法的设计和数值实验效果的比较,理论研究则很少,本文作者给出了一种求解多目标优化问题的新遗传算法
(RMOGA) ,并用Markov 链的理论对RMOGA 的收敛性进行了研究,其结果表明RMOGA 依概率收敛到问题的
Pareto 前沿面-Population-based genetic algorithm search for multi-objective optimization probl
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This a simple genetic algorithm program for finding minimizers of a function. I wrote this in 1999 when I was interested in aerodynamic optimization problems. I think that genetic algorithm is a very interesting optimization algorithm.-This is a simp
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针对传统遗传算法的早熟收敛问题,在著名的“基因块”假设的基础上,提出了一种改进算法：利用设计的新算子对传统遗传算法演化过程中被淘汰的个体进行二次演化，使得可能包含在将来的演化中对结果的全局最优性产生重要影响的基因块得以保留,以此来避免遗传算法早熟收敛现象。实验结果证明了该改进算法可以有效地避免早熟收敛，提高了算法全局优化能力。-Premature convergence of traditional genetic algorithm, based on the assumptions of t
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遗传算法优化神经网络程序-Genetic algorithm optimization neural network program-Genetic algorithm optimization neural network program
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matlab遗传算法工具箱解函数优化问题应用实例-matlab genetic algorithm toolbox solution function optimization application examples
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一船算法优化 TSP用的各种算子 置换变异算子和杂交算子-A boat algorithm to optimize the TSP with a variety of operator replacement mutation operator and crossover operator
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本程序详细讲解了关于遗传算法的优化问题，对于学习遗传算法帮助很大-This procedure gave a detailed account on the genetic algorithm optimization problems, very helpful for learning genetic algorithm
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利用遗传算法求解最优化问题，在一定的条件下，求解目标函数的最优化问题-Genetic Algorithm optimization problems under certain conditions, to solve the optimization problem of the objective function
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遗传算法优化,遗传算法基本原理程序应用举例-Optimization genetic algorithm
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采用遗传算法和例子群算法进行优化，可以采用试验设计方法构建试验样本，用Kriging方法构建适应度函数，然后进行优化求解，记住，采用此程序是，应该安装Kring工具箱子-Using genetic algorithm and example of algorithm optimization, experimental design method can be used to build the test sample, with the Kriging method constructing
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几种最新智能优化算法的改进与应用的源代码，包括人工蚁群、遗传算法优化神经网络-Several of the latest intelligent optimization algorithm improvement and application source code, including artificial ant colony, genetic algorithm optimization of neural networks, etc.
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In computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to generate h
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