Description: This directory contains the Genetic Algorithm Optimization Toolbox for
Matlab 7.
To use this, if you are local to NCSU and have AFS access to this
directory, simply extend the matlab path using the following command.-This directory contains the Genetic Algor ithm Optimization Toolbox for Matlab 7. To use t his, if you are local to NCSU and have access to AFS Thi s directory, simply extend the path using the Matlab followi ng command. Platform: |
Size: 22764 |
Author:顾同止 |
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Description: 遗传算法优化工具箱介绍及实例源程序,适合初学者用matlab进行遗传算法的学习-genetic algorithm optimization toolbox introduced and examples of source, for beginners using Matlab for the study of genetic algorithms Platform: |
Size: 105042 |
Author:田园 |
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Description: This directory contains the Genetic Algorithm Optimization Toolbox for
Matlab
To use this, if you are local to NCSU and have AFS access to this
directory, simply extend the matlab path using the following command.
You can also place this command in a file called startup.m. Everytime
you start Matlab in the directory containing this file, the path will
always be extended. Platform: |
Size: 106941 |
Author:张志 |
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Description: 遗传算法优化工具箱介绍及实例源程序,适合初学者用matlab进行遗传算法的学习-genetic algorithm optimization toolbox introduced and examples of source, for beginners using Matlab for the study of genetic algorithms Platform: |
Size: 104448 |
Author:田园 |
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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: |
Size: 210944 |
Author:icyrock |
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Description: This demo shows how to use MATLAB, Optimization Toolbox, and Genetic Algorithm and Direct Search Toolbox to optimize the design of a double wishbone suspension system. Platform: |
Size: 2056192 |
Author:阳关 |
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Description: This directory contains the Genetic Algorithm Optimization Toolbox for
Matlab
To use this, if you are local to NCSU and have AFS access to this
directory, simply extend the matlab path using the following command.
You can also place this command in a file called startup.m. Everytime
you start Matlab in the directory containing this file, the path will
always be extended. Platform: |
Size: 106496 |
Author: |
Hits:
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: |
Size: 269312 |
Author:dh |
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Description: 介绍了遗传算法的基本原理和求解流程, 详细阐述了Matlab 遗传算法工具箱的使用方法, 并通过使用遗传算法工具箱对一个典型的函数优化问题进行求解, 验证了该工具箱在解决函数优化问题上的有效性和实用性。-Introduce a genetic algorithm to solve the basic principle and flow in detail Matlab genetic algorithm toolbox to use, and by using genetic algorithm toolbox for a typical function optimization problems to solve, the validity of the toolbox in solving function optimization problems on the effectiveness and practicality. Platform: |
Size: 51200 |
Author:崔艳 |
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Description: This a demonstration of how to find a minimum of a non-smooth
objective function using the Genetic Algorithm (GA) function in the
Genetic Algorithm and Direct Search Toolbox. Traditional derivative-based
optimization methods, like those found in the Optimization Toolbox, are
fast and accurate for many types of optimization problems. These methods
are designed to solve smooth , i.e., continuous and differentiable,
minimization problems, as they use derivatives to determine the direction
of descent. While using derivatives makes these methods fast and
accurate, they often are not effective when problems lack smoothness,
e.g., problems with discontinuous, non-differentiable, or stochastic
objective functions. When faced with solving such non-smooth problems,
methods like the genetic algorithm or the more recently developed pattern
search methods, both found in the Genetic Algorithm and Direct Search
Toolbox, are effective alternatives. -This is a demonstration of how to find a minimum of a non-smooth
objective function using the Genetic Algorithm (GA) function in the
Genetic Algorithm and Direct Search Toolbox. Traditional derivative-based
optimization methods, like those found in the Optimization Toolbox, are
fast and accurate for many types of optimization problems. These methods
are designed to solve smooth , i.e., continuous and differentiable,
minimization problems, as they use derivatives to determine the direction
of descent. While using derivatives makes these methods fast and
accurate, they often are not effective when problems lack smoothness,
e.g., problems with discontinuous, non-differentiable, or stochastic
objective functions. When faced with solving such non-smooth problems,
methods like the genetic algorithm or the more recently developed pattern
search methods, both found in the Genetic Algorithm and Direct Search
Toolbox, are effective alternatives. Platform: |
Size: 18432 |
Author:gao |
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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: |
Size: 9216 |
Author:FZenjoys |
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Search - genetic algorithm OPTIMIZATION TOOLBOX