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[SourceCode] 二进制nsga-ii DL : 0: 二进制nsga-ii
Update : 2011-03-21 Size : 7.76kb Publisher : maoyunfei
[SourceCode] NSGA-II-matlab DL : 5: NSGA-II-matlab内含matlab编写的NSGA2 程序和相关的PDF说明
Update : 2011-05-24 Size : 7.31kb Publisher : xiongjian0
[matlab] NSGA-II DL : 0: 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
Update : 2025-02-19 Size : 148kb Publisher : 王军
[AI-NN-PR] NSGA-II DL : 1: NSGA-II遗传算法的文档，里面的内容比较好理解，是学习遗传算法的必备知识-Genetic Algorithm NSGA-II of the document, which is better understanding of the content is a genetic algorithm to learn the knowledge necessary
Update : 2025-02-19 Size : 346kb Publisher : zhang
[AI-NN-PR] MOEA-NSGA-II DL : 0: NSGA-II多目标优化的matlab代码-NSGA-II multi-objective optimization matlab code
Update : 2025-02-19 Size : 362kb Publisher : gitry
[AI-NN-PR] NSGA-II DL : 1: 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.
Update : 2025-02-19 Size : 375kb Publisher : feishao
[matlab] MOEA-NSGA-II DL : 0: 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
Update : 2025-02-19 Size : 379kb Publisher : zhizhou
[AI-NN-PR] Deb_NSGA-II DL : 0: 基于MATLAB平台的Deb多目标遗传算法之NSGA-II，包含帮助文件-Deb based on MATLAB platform of multi-objective genetic algorithm NSGA-II, contains the Help files
Update : 2025-02-19 Size : 168kb Publisher : zangtianlei
[AI-NN-PR] NSGA-II(2000) DL : 1: 这是多目标优化问题的经典文章，值得研究。A Fast and Elitist Multi-Objective Genetic Algorithm NSGA-II (2000)-A Fast and Elitist Multi-Objective Genetic Algorithm NSGA-II (2000)
Update : 2025-02-19 Size : 1.04mb Publisher : Winjade
[AI-NN-PR] NSGA-II DL : 1: 外国人编写的有用的 NSNA-II程序有详细的文档说明-NSGA ( [5]) is a popular non-domination based genetic algorithm for multi- objective optimization. It is a very e® ective algorithm but has been generally criticized for its computational complexity
Update : 2025-02-19 Size : 161kb Publisher : 炯炯
[matlab] NSGA-II DL : 0: NSGA-II源程序,用于求解多目标优化问题，是对NSGA在非支配集构造方法，维持解分布性策略等方面进行的改进。-NSGA-II source code for multi-objective optimization problem, NSGA is a non-dominated set in the constructor, maintenance solutions and other aspects of the distribution strategy of improvement.
Update : 2025-02-19 Size : 37kb Publisher : 于明
[matlab] NSGA-II DL : 0: 算法实现完整代码，非支配排序，拥挤距离排序(NSGA-II complete no-dominated sort and corwding distance sort you can use your algorithm to improve your algorithm)
Update : 2025-02-19 Size : 2kb Publisher : guoneng12355
[matlab] nsga-ii.rar DL : 0: 这个是关于nsga-ii的代码，有兴趣的可以看一下，，，(this is the code of nsga-ii)
Update : 2025-02-19 Size : 2kb Publisher : xiaoguangge
[matlab] NSGA-II完整版 DL : 0: NSGA-II完整版代码包括非支配排序和聚集距离的计算(NSGA-II code Including the calculation of non-dominated ordering and gathering distance)
Update : 2025-02-19 Size : 2.24mb Publisher : feng711
[Other] NSGA-II FOR C++ DL : 0: NSGA-II, 多目标遗传算法，适用于C/C++平台(NSGA-II A multi-objective optimization algorithm)
Update : 2025-02-19 Size : 1kb Publisher : Fiona。。。
[AI-NN-PR] NSGA-II DL : 0: NSGA-ii算法，一种基于拥挤度的非支配排序遗传算法(NSGA-ii algorithm, a non-dominated sorting genetic algorithm based on congestion degree)
Update : 2025-02-19 Size : 449kb Publisher : Zanesheng
[matlab] NSGA-II源程序 DL : 0: MATLAB智能算法NSGA-II可实现，亲测可用(The intelligent algorithm NSGA-II of MATLAB can be realized and the pro-test can be used.)
Update : 2025-02-19 Size : 34kb Publisher : 搞.不懂
[matlab] NSGA-II for Scheduling DL : 1: 利用Matla编写的NSGA-II算法，用于求解车间调度的多目标问题(The NSGA-II algorithm written by Matla is used to solve the multi-objective problem of job shop scheduling.)
Update : 2025-02-19 Size : 8kb Publisher : TXC2
[Other] YPEA120 NSGA-II DL : 0: NSGA-II的MATLAB代码，直接运行main.m文件就行，建议最好有matlab的基础(Matlab code of NSGA-II,The matlab code of NSGA-II, just run the main. M file directly, it is recommended to have the basis of MATLAB)
Update : 2025-02-19 Size : 9kb Publisher : 江的学习
[matlab] choxiao-NSGA-II DL : 0: 测试nsga2的优化性能,包含zdt系列、sch系列，支持三个目标下的约束求解(NSGA-II TEST,including zdt series,sch series and is okay for a 3-dimensional minimization problem.)
Update : 2025-02-19 Size : 1.05mb Publisher : choxiao

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