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: 将博弈理论与演化算法结合起来,开发了一种新进化优化的算法-of Game Theory and combining evolutionary algorithm, the development of a new evolutionary optimization algorithm Platform: |
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Author:刘伟兵 |
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Description: 针对TSP问题,提出了一种改进的遗传算法。在遗传算法中引入进化算法的思想,在此基础上提出顶端培育策略和分阶段策略,以求在保证群体多样性的同时加快收敛速度。-against TSP, an improved genetic algorithms. Genetic Algorithm evolutionary algorithm introduced the idea that the basis of this proposed strategy and cultivating top phased strategy groups in order to ensure diversity at the same time speed up the convergence. Platform: |
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Description: 蚁群算法是模仿真实的蚁群行为而提出的一种模拟进化算法,蚂蚁之间是通过一种信息素的物质传递信息的,蚂蚁在运动的过程中能够在经过的路径上留下该物质,而且能够感知这种物质的存在及其强度,并以此指导自己的运动方向。它是一种通过类比组合优化和蚁群觅食行为而构造的一种算法,可以用来解决各种组合优化问题,本代码用来解决生产调度问题-Ant colony algorithm is based on real ant colony behavior and proposed a simulated evolutionary algorithm, ants are among the pheromone through a material and impart information, ants in the process of movement in the path on the left of the substance , but also perceived the existence of such material and its strength, and to guide their direction. By analogy it is a combinatorial optimization and ant colony foraging behavior and structure of an algorithm can be used to solve various combinatorial optimization problems, the code used to solve the production scheduling problem Platform: |
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Author:穆海华 |
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Description: 在工业工程中,许多最优化问题性质十分复杂,很难用传统的优化方法来求解.自1960年以来,人们对求解这类难解问题日益增加.一种模仿生物自然进化过程的、被称为“进化算法(evolutionary algorithm)”的随机优化技术在解这类优化难题中显示了优于传统优化算法的性能。目前,进化算法主要包括三个研究领域:遗传算法、进化规划和进化策略。其中遗传算法是迄今为止进化算法中应用最多、比较成熟、广为人知的算法。-In industrial projects, many of the optimization problem very complex nature, it is difficult using traditional optimization methods to solve. Since 1960, people have to solve such difficult problems is growing. A mimic natural biological evolution, and was said as Platform: |
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Author:starboy_2nd |
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Description: 这是一本讲微分进化的书,进化算法是以遗传算法为代表的一类随机算法的总称,95年由Rainer Storn和Kenneth Prici提出微分进化方法,比传统进化算法更好更简单,2004年该方法的原创者出版了长达580页的微分进化:一种全局优化的实用方法,本书是英文版,似乎还没有中文版,希望对感兴趣的人有用-This is a book stresses differential evolution, evolutionary algorithm based on genetic algorithm to represent a class of random algorithm collectively, 95 by Rainer Storn and Kenneth Prici proposed differential evolution approach, better than the traditional evolutionary algorithm simpler, 2004 The method of the originators of the publication of up to 580 of the differential evolution: A practical method for global optimization, this book is the English version seems to have been the Chinese version, in the hope that people interested in useful Platform: |
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Description: 微粒群算法[PSO ] 是由Kennedy 和Eberhart等于1995 年开发的一种演化计算技术, 来源于对鸟群捕食过程的模拟。PSO同遗传算法类似,是一种基于叠代的优化工具,但与遗传算法使用遗传操作子进行优化不同,利用群体中各个体之间的“协作”与“竞争”关系,根据自身及其竞争者的飞行经验,调整自己的行为。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] are equal by Kennedy and Eberhart in 1995 developed an evolutionary computing technology, from preying on the birds of the simulation process. PSO with genetic algorithm is similar to an iterative optimization-based tool, but the use of genetic algorithms and genetic manipulation of different sub-optimize the use of groups between the various entities within the " collaboration" and " competitive" relationship, according to themselves and their competition the flying experience, adjust their behavior. Comparison with genetic algorithms, PSO has the advantage of being simple and easy and did not realize the need to adjust the parameters much. Has been widely applied to function optimization, neural network training, fuzzy system control, as well as other genetic algorithm applications. Platform: |
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Author:wzy |
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Description: 遗传算法(Genetic Algorithm)是模拟达尔文生物进化论的自然选择和遗传学机理的生物进化过程的计算模型,是一种通过模拟自然进化过程搜索最优解的方法,它最初由美国Michigan大学J.Holland教授于1975年首先提出来的,并出版了颇有影响的专著《Adaptation in Natural and Artificial Systems》,GA这个名称才逐渐为人所知,J.Holland教授所提出的GA通常为简单遗传算法(SGA),遗传算法简单源程序。-Genetic Algorithm (Genetic Algorithm) is a simulation of the biological theory of evolution Darwin' s natural selection and genetic mechanism of the process of biological evolution computing model is a natural evolutionary process by simulating the optimal solution search methods, it was first introduced by J. Holland United States University of Michigan Professor in 1975, first put forward, and published influential monographs " Adaptation in Natural and Artificial Systems" , GA gradually known the name, J. Holland, Professor of GA are usually made by a simple genetic algorithm (SGA ), a simple genetic algorithm source code. Platform: |
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Author:周武静 |
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Description: 量子进化算法论文,详尽介绍该算法的原理及实验结果-Quantum evolutionary algorithm papers, detailed descriptions of the principle of the algorithm and experimental results Platform: |
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Author:向健 |
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Description: 细菌觅食随机优化论文及matlab源码。该算法属于进化算法的一种,可以处理全局优化、多目标优化、约束优化和动态优化等问题。-Bacterial feeding stochastic optimization papers and matlab source code. The algorithm belongs to a kind of evolutionary algorithm that can deal with global optimization, multi-objective optimization, constrained optimization and dynamic optimization problems. Platform: |
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Author:bxingliu |
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Description: 进化算法及其在全局优化和VRP中的应用的毕业论文-Evolutionary Algorithm and Its
Application in GlobalOptimization and Vehicle Routing Problem Platform: |
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Author:炯炯 |
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Description: spea2多目标进化算法对两个目标的多目标优化问题的测试-spea2 multi-objective evolutionary algorithm on the two goals of testing multi-objective optimization problem Platform: |
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Author:徐志丹 |
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Description: 遗传算法(Genetic Algorithm)是模拟达尔文生物进化论的自然选择和遗传学机理的生物进化过程的计算模型,是一种通过模拟自然进化过程搜索最优解的方法,它最初由美国Michigan大学J.Holland教授于1975年首先提出来的,并出版了颇有影响的专著《Adaptation in Natural and Artificial Systems》,GA这个名称才逐渐为人所知,J.Holland教授所提出的GA通常为简单遗传算法(SGA)。
-In artificial intelligence, an evolutionary algorithm (EA) is a subset of evolutionary computation, a generic population-based metaheuristic optimization algorithm. An EA uses some mechanisms inspired by biological evolution: reproduction, mutation, recombination, and selection. Candidate solutions to the optimization problem play the role of individuals in a population, and the fitness function determines the environment within which the solutions "live" (see also cost function). Evolution of the population then takes place after the repeated application of the above operators. Artificial evolution (AE) describes a process involving individual evolutionary algorithms EAs are individual components that participate in an AE.
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Author:李际超 |
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Description: 简要阐述了进化算法的基本原理 ,探讨了在 MATLAB 环境中实现遗传算法各算子的编程方法 , 并以一个简单的实例说明所编程序在函数全局寻优中的应用。 -Briefly the basic principles of evolutionary algorithm, to explore the genetic algorithm in MATLAB programming methods for each operator, and a simple example to illustrate the application of programmable function global optimization. Platform: |
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Author:张嘉城 |
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Description: 粒子群算法源程序,是近年来发展起来的一种新的进化算法。有实现容易、精度高、收敛快等优点。是一种并行算法。-Particle swarm algorithm source code, is a new evolutionary algorithm developed in recent years. There are easy to implement, high precision, fast convergence and so on. Is a kind of parallel algorithms. Platform: |
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Author:Mickel |
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Description: 本章将主要介绍思维进化算法的基本思想,并结合非线性函数拟合实际案例,在MATLAB环境下实现思维进化算法。-This chapter will mainly introduce the basic idea of mind evolutionary algorithm, and combining with the case, the nonlinear function fitting implement mind evolutionary algorithm in MATLAB environment. Platform: |
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Author:恒之毅的天空 |
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