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Description: NSGA-II-matlab内含matlab编写的NSGA2 程序和相关的PDF说明
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Size: 7489 |
Author: xiongjian0 |
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Description: 基于进化算法的多目标优化,以matlab程式所寫成,請大家參考參考-evolutionary algorithm based on the multi-objective optimization to written Matlab program, please refer to reference
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Size: 371712 |
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Description: 基于ＮＳＧＡ方法的多目标遗传算法程序,本程序为通用包,可自行修改.-NSGA method based on multi-objective Genetic Algorithms procedures, the procedures for the general packet may amend its own.
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Size: 4096 |
Author: 许峰 |
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Description: 多目标优化进化算法目前公认效果收敛性最好的算法NSGA2源码，内有多目标算法的工具箱，对实现其他多目标优化算法很有帮助-Multi-objective optimization evolutionary algorithm is currently recognized as the effect of convergence of the algorithm NSGA2 best source, with a number of target algorithm toolbox for achieving the other multi-objective optimization algorithm for helpful
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Size: 370688 |
Author: wy |
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Description: NSGA原代码，很多人在找这个，对搞智能优化很有帮助-NSGA original code, a lot of people looking for this, very helpful to engage in intelligent optimization
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Size: 151552 |
Author: 王军 |
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Description: 现有的PID参数优化方法往往难以同时兼顾系统对快速性、稳定性与鲁棒性的要求，本文针对这一缺陷，提出了一种多目标PID优化设计方法——在满足系统的鲁棒性的前提下，以超调量、上升时间和调整时间最小作为多目标优化的子目标，并将NSGA-Ⅱ与PGA相结合对其求解。该算法求得的Pareto最优解分布均匀，收敛性和鲁棒性好，决策者可根据实际系统的要求在Pareto解集中选择最终的满意解，这为快速性、稳定性与鲁棒性的权衡分析提供了有效的工具。仿真结果表明本文设计方法的有效性和优越性。
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Size: 1024 |
Author: zzh |
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Description: nsga是用于多目标计算的源程序！非常的好用！-nsga is calculated for multi-objective source! Very easy to use!
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Size: 828416 |
Author: fujia |
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Description: matlab实现最优化选择的一个算法，大家可以下下来参考，我也是从别处down的，谢谢原作者-matlab optimize the choice of an algorithm, we can refer to the next down, I am also down elsewhere, thank you, original author
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Size: 371712 |
Author: haha |
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Description: 实现了多目标遗传算法NSGA2，并带有详细注释及相关论文，读者只需根据具体问题简要修改，即可使用。-Achieved a multi-objective genetic algorithm NSGA2, with detailed notes and related papers, the reader just a brief specific issues in accordance with changes to use.
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Size: 126976 |
Author: 赵爽 |
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Description: NSGA-II多目标优化的matlab代码-NSGA-II multi-objective optimization matlab code
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Size: 370688 |
Author: gitry |
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Description: 一个matlab环境下编制的使用很方便的多目标程序-The preparation of a matlab environment is very convenient to use multi-objective procedure
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Size: 10109952 |
Author: marry |
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Description: 利用MATLAB编写的简单的NSGA2程序 ,实用方便 -Prepared using a simple MATLAB program NSGA2, practical convenience
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Size: 20480 |
Author: 最爱爽肤水 |
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Description: NSGA-2 一种非常强大的多目标遗传算法,本人已经把它调通.-NSGA-2 a very strong multi-objective genetic algorithm, I have to tune it pass.
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Size: 384000 |
Author: feishao |
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Description: 多目标遗传算法通用编程包，是解决复杂多目标问题的通用程序-MOEA-NSGA
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Size: 388096 |
Author: zhizhou |
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Description: MATLAB的NSGA改进后的算法-MATLAB' s NSGA improved algorithm
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Size: 1021952 |
Author: vanderveer |
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Description: 多目标优化经典算法之一，NSGA2算法，用Matlab写的，好好学一下-One of the classical multi-objective optimization algorithm, NSGA2 algorithm, written using Matlab, a good school look
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Size: 154624 |
Author: caiqing |
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Description: 最权威版nsga2的matlab版 ，国际EMOO研发小组的成果。-The most authoritative version of nsga2 the matlab version of the results of the international EMOO development team.
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Size: 7168 |
Author: wsf211 |
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Description: genetic algorithm program for power system
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Size: 375808 |
Author: sumit |
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Description: matlab编写的基于粒子群优化算法的多目标优化，可以处理电力系统优化问题-matlab write PSO-based multi-objective optimization, can handle the power system optimization problems
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Size: 370688 |
Author: jihai77007 |
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Description: 测试可以跑，根据自己情况修改下函数即可. NSGA-III 首先定义一组参考点。然后随机生成含有 N 个（原文献说最好与参考点个数相同）个体的初始种群，其中 N 是种群大小。接下来，算法进行迭代直至终止条件满足。在第 t 代，算法在当前种群 Pt的基础上，通过随机选择，模拟两点交叉（Simulated Binary Crossover，SBX）和多项式变异 产生子代种群 Qt。Pt和 Qt的大小均为 N。因此，两个种群 Pt和 Qt合并会形成种群大小为 2N 的新的种群 Rt=Pt∪Qt。 为了从种群 Rt中选择最好的 N 个解进入下一代，首先利用基于Pareto支配的非支配排序将 Rt分为若干不同的非支配层（F1，F2等等）。然后，算法构建一个新的种群St，构建方法是从 F1开始，逐次将各非支配层的解加入到 St，直至 St的大小等于 N，或首次大于 N。假设最后可以接受的非支配层是 L层，那么在 L+ 1 层以及之后的那些解就被丢弃掉了，且 St\ FL中的解已经确定被选择作为 Pt+1中的解。Pt+1中余下的个体需要从 FL中选取，选择的依据是要使种群在目标空间中具有理想的多样性。(The test can run and modify the function according to its own situation. NSGA-III first defines a set of reference points. Then the initial population containing N individuals (preferably the same number of reference points as the original literature) was randomly generated, where N was the size of the population. Next, the algorithm is iterated until the termination condition is satisfied. On the basis of current population Pt, the algorithm simulates two-point crossover (SBX) and polynomial mutation to produce offspring population Qt by random selection.)
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Size: 14336 |
Author: 朱朱521 |
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