Description: 粒子群优化算法(PSO)是一种进化计算技术(evolutionary computation).源于对鸟群捕食的行为研究 PSO同遗传算法类似，是一种基于叠代的优化工具。系统初始化为一组随机解，通过叠代搜寻最优值。但是并没有遗传算法用的交叉(crossover)以及变异(mutation)。而是粒子在解空间追随最优的粒子进行搜索。详细的步骤以后的章节介绍 同遗传算法比较，PSO的优势在于简单容易实现并且没有许多参数需要调整。目前已广泛应用于函数优化，神经网络训练，模糊系统控制以及其他遗传算法的应用领域-Particle Swarm Optimization (PSO) is an evolutionary technology (evolutionary computation). Predatory birds originated from the research PSO with similar genetic algorithm is based on iterative optimization tools. Initialize the system for a group of random solutions, through iterative search for the optimal values. However, there is no genetic algorithm with the cross- (crossover) and the variation (mutation). But particles in the solution space following the optimal particle search. The steps detailed chapter on the future of genetic algorithm, the advantages of PSO is simple and easy to achieve without many parameters need to be adjusted. Now it has been widely used function optimization, neural networks, fuzzy systems control and other genetic algorithm applications Platform: |
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Description: ：Matlab遗传算法(GA)优4~-r-具箱是基于基本操作及终止条件、二进制和十进制相互转换等操作的综合
函数库。其实现步骤包括：通过输入及输出函数求出遗传算法主函数、初始种群的生成函数，采用选择、交叉、变异
操作求得基本遗传操作函数。以函数仿真为例，对该函数优化和GA改进，只需改写函数m文件形式即可。-: Matlab genetic algorithm (GA) U 4 ~-r-a box is based on the basic operation and termination conditions, binary and decimal conversion operation, such as a comprehensive function library. The realization of these steps include: input and output functions through the genetic algorithm to derive the main function, initial population generation function, the use of selection, crossover, mutation operation to achieve the basic function of genetic manipulation. Simulation in order to function as an example, the GA function optimization and improvement, just rewritten m the form of a document can function. Platform: |
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Author:icyrock |
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Description: ：介绍遣传算法的基本原理和Matlab的遗传算法优化工具箱(GAOT)，分析了优化工具函数。探讨Matlab遗传算法工具箱在
参数优化和非线性规划中的应用。通过优化实例，说明遗传算法是一种具有良好的全局寻优性能的优化方法。用Maflab语
言及Maflab语言编制的优化工具箱进行优化设计具有语言简单、函数丰富、用法比较灵活、编程效率高等特点。-: Removal algorithm introduce the basic principles and Matlab Genetic Algorithm Optimization Toolbox (GAOT), an analysis of function optimization tool. Explore the Matlab Genetic Algorithm Toolbox in the parameter optimization and nonlinear programming applications. Through optimization examples to illustrate the genetic algorithm is a good global optimization method to optimize performance. Maflab language and using language Maflab Optimization Toolbox to optimize the design of the language is simple, function-rich, and using more flexible programming and high efficiency. Platform: |
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Description: 二进制编码遗传算法求函数极大值，实现Rosenbrock函数极大值优化计算的二进制编码遗传算法
-Binary-coded genetic algorithm for maximum function, Rosenbrock function to achieve maximum optimization of the calculation of the binary-coded genetic algorithm Platform: |
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Author:纷纷 |
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Description: GA（Simple Genetic Algorithm）是一种强大的智能多变量优化算法，它模仿种群繁殖规律来进行优化。
本SGA可以优化变量，求最小值,最大值（当把函数倒数也就求最小值啦）
并且支持浮点编码，grey编码，二进制编码；轮赌法选择，锦标赛选择；单点交叉，均布交叉，浮点交叉；单点变异，浮点变异；-GA (Simple Genetic Algorithm) is a powerful, intelligent multi-variable optimization algorithms, which mimic the breeding populations of the law to be optimized. SGA can optimize this variable, and the minimum value, maximum value (when the function of the countdown you will seek the minimum value) and to support the floating-point encoding, grey code, binary code round of gambling options, tournament selection single-point crossover, uniform Cross, floating-point crossover single point mutation, floating-point variation Platform: |
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Author:yuandi |
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Description: 用MA TLAB 语言及MA TLAB 语言编制的优化工具箱进行优化设计具有语言简单、函数丰富、用法比
较灵活、编程效率高等特点. 本文对遗传算法和基于MA TLAB 的遗传算法优化工具箱(GAO T ) 作了简要的介
绍、分析了优化工具函数, 并结合非线性、多峰值函数问题的优化实例, 说明了遗传算法是一种具有良好的全局
寻优性能的优化方法.-MA TLAB with language and language of the MA TLAB optimization toolbox to optimize the design of the language is simple, function-rich, and using more flexible programming and high efficiency. In this paper, genetic algorithm and MA TLAB based on genetic algorithm optimization toolbox (GAO T ) gave a brief introduction, an analysis of function optimization tool, combined with non-linear, multimodal function optimization problem examples to illustrate the genetic algorithm is a good global optimization method to optimize performance. Platform: |
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Description: 常用matlab遗传算法目标函数的编写实例，如：双积分优化，收获系统，装载系统等-Matlab genetic algorithm commonly used objective function of the preparation of examples, such as: double-integrating optimization, harvest systems, loading systems, etc. Platform: |
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Author:熊梅西 |
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Description: yj1.m：简单一元函数优化实例，利用遗传算法计算下面函数的最大值
包括了遗传算法的12个经典例题，适合大家学习参考。-yj1.m: a dollar a simple example of function optimization using genetic algorithm function below the maximum value of the genetic algorithm including 12 classic example for everyone to learn the reference. Platform: |
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Author:肖明 |
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Description: 包含大量遗传算法程序，还有部分PID参数优化函数，希望对朋友们有用。-Contains a large amount of genetic algorithm procedure, part of PID parameter optimization function, in the hope that useful friends. Platform: |
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Author:gengbin |
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Description: 有关链路容量和流量优化分配的遗传算法
函数功能
使用遗传算法求解通信网链路容量和流量联合优化分配问题-Related to link capacity and flow of genetic algorithm to optimize the distribution function using genetic algorithm function communication network link capacity and traffic distribution of the joint optimization Platform: |
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Author:huangmeichun |
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Description: 基于遗传算法的函数优化，利用遗传算法求出目标函数的最优值，适合初学matlab和遗传算法的学者下载学习。-The function of the genetic algorithm-based optimization, using genetic algorithms to determine the optimal value of the objective function, suitable for beginners of Matlab and genetic algorithm scholars download learning. Platform: |
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Description: 遗传算法提供了求解非线性规划的通用框架，它不依赖于问题的具体领域。遗传算法的优点是将问题参数编码成染色体后进行优化， 而不针对参数本身， 从而不受函数约束条件的限制； 搜索过程从问题解的一个集合开始， 而不是单个个体， 具有隐含并行搜索特性， 可大大减少陷入局部最小的可能性。而且优化计算时算法不依赖于梯度信息，且不要求目标函数连续及可导，使其适于求解传统搜索方法难以解决的大规模、非线性组合优化问题。(Genetic algorithm provides a general framework for solving nonlinear programming, which does not depend on the specific problem domain. The advantage of genetic algorithm is that the problem parameters are encoded into chromosomes for optimization, rather than the parameters themselves. The search process starts from a set of problem solutions, rather than a single individual, and has the implicit parallel search feature, which can greatly reduce the possibility of falling into the local minimum. Moreover, the algorithm does not rely on gradient information and does not require the objective function to be continuous and differentiable, which makes it suitable for solving large-scale and nonlinear combinatorial optimization problems that are difficult to be solved by traditional search methods.) Platform: |
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Author:FZenjoys |
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Description: Matlab 遗传算法(Genetic Algorithm)优化工具箱是基于基本操作及终止条件、二进制和十进制相互转换等操作的综合函数库。其实现步骤包括：通过输入及输出函数求出遗传算法主函数、初始种群的生成函数，采用选择、交叉、变异操作求得基本遗传操作函数。以函数仿真为例，对该函数优化和GA 改进，只需改写函数m 文件形式即可。(The Matlab Genetic Algorithm optimization toolbox is a comprehensive function library based on basic operations and termination conditions, binary and decimal conversion and other operations. The implementation steps include: the main function of genetic algorithm and the generation function of the initial population are obtained by the input and output functions, and the basic genetic operation function is obtained by the selection, crossover and mutation operations. Taking function simulation as an example, the function optimization and GA improvement only need to rewrite function m file form) Platform: |
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