搜索资源列表
MOEA-NSGA-II
- 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
nsga_2
- 基于非支配排序遗传算法处理多目标优化的matlab例程,可以自行修改-Based on NSGA handling multi-objective optimization of Matlab routines, can make its own decisions
nsga2_Matlab_xixilee
- 对多目标优化算法NSGA-II算法的改进，该算法进化代数少，但是获得的最终效果特别好！-pair of multi-objective optimization algorithm NSGA-II algorithm, the algorithm evolutionary less algebra, However, the ultimate effect was particularly good!
MOEA-NSGA-II
- 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 ta
optipid
- 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
NSGA2-dynamic
- 多目标优化进化算法目前公认效果收敛性最好的算法NSGA2c++源码,具有一般性，可在此基础上继续改进，对实现其他多目标优化算法很有帮助.-Multi-objective optimization evolutionary algorithm is currently the best recognized effect of convergence of the algorithm NSGA2c++ Source, with the g
nsga2_c_source
- 实现遗传算法（GA）的多目标优化算法：NSGA-II算法。-The realization of genetic algorithms (GA) of the multi-objective optimization algorithm: NSGA-II algorithm.
NSGAII
- 实现遗传算法（GA）的多目标优化算法：NSGA-II的MATLAB程序-The realization of genetic algorithms (GA) of the multi-objective optimization algorithm: NSGA-II of the MATLAB program
MOEA-NSGA-II
- NSGA-II多目标优化的matlab代码-NSGA-II multi-objective optimization matlab code
MOEA-D-Continuous
- 多目标优化程序，国际顶级期刊IEEE EC 经典算法-multi-objective optimization algorithm presented in journal of IEEE trans
Standard_evolutionary_algorithm_design_and_analysi
- 为了有效检测多目标优化进化算法的性能，从3 个方面进行多目标优化测试问题的设计，即约束条件、最优解分布的均匀性、算 法逼近Pareto 最优前沿的难度，采用NSGA-Ⅱ算法对这些测试问题进行仿真实验，并将算法求得的最优解可视化。结果显示，测试问题能够有效检测算法在上述3 方面的性能。-In order to effectively detect the multi-objective optimization evolutionar
NSGA-II
- 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 distri
NSGA
- 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
nsga-ii
- nsga-2多目标优化经典算法，有图并亲测已经跑通，供初学者学习(NSAG-2 multi-objective optimization of the classic algorithm, there are diagrams and pro test run, for beginners to learn)
多目标遗传算法matlab程序
- 多目标遗传算法，实现多目标优化,优化结束之后可用topsis方法进行选取(NSGA 2 ,After the optimization can be used topsis method to select)
NSGA-II
- 多目标优化问题，文献参考，A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimization(multi-object optimization)
NSGA-II
- matlab实现的多目标优化遗传算法代码。可输出结果并画图。(The matlab program of NSGA-II.)
NSGAⅡ
- 利用NSGAⅡ算法处理多目标优化问题，测试函数包括ZDT1,2,3; DTLZ1,2,3。包含测试函数的真实前沿面数据。(NSGA II algorithm is used to deal with multi-objective optimization problems. The test functions include ZDT1,2,3 and DTLZ1,2,3. Contains the real frontier dat
多目标NSGA
- NSGA（非支配排序遗传算法）、NSGA-II（带精英策略的快速非支配排序遗传算法），都是基于遗传算法的多目标优化算法，是基于pareto最优解讨论的多目标优化。(NSGA (Non-dominated Sorting Genetic Algorithms) and NSGA-II (Quick Non-dominated Sorting Genetic Algorithms with Elite Strategy) are multi
遗传算法多目标优化模板
- 利用geatpy库是实现多目标优化， 基于改进NSGA-Ⅱ算法求解多目标优化问题的进化算法模板，传统NSGA-Ⅱ算法的帕累托最优解来只源于当代种群个体，这样难以高效地获取更多的帕累托最优解，同时难以把种群大小控制在合适的范围内，改进的NSGA2整体上沿用传统的NSGA-Ⅱ算法，不同的是，该算法通过维护一个全局帕累托最优集来实现帕累托前沿的搜索，故并不需要保证种群所有个体都是非支配的。(Using geatpy library to re