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
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
MOEA-NSGA-II.zip
- 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
MOEA-NSGA-II.zip
- 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
MOEA-NSGA-II.rar
- NSGA-II多目标优化的matlab代码,NSGA-II multi-objective optimization matlab code
MOEA
- 本例程解决了一个两个目标的优化问题，采用的是权重系数法求解。求解过程中采用了代沟。程序中有详细的注释-This routine solves a two-goal optimization problem, using the weight coefficient method. Solving process used in the generation gap. Procedures are detailed in the Notes
MOEA-NSGA-II
- genetic algorithm, simulated annealing, singleobjective, particle swarm optimi..., optimization, classes
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
MOEA-NSGA-II
- genetic algorithm program for power system
(DE)MOEA-NSGA-II
- nsga2与DE算法的结合算法,用于求解多目标优化问题-the combination of nsga2 algorithm with DE algorithm
MOEA-NSGA-II.zip
- 多目标的经典遗传算法MOEA-NSGA-II，采用平衡集与非支配排序方法,Classic multi-objective genetic algorithm MOEA-NSGA-II, using the non-dominated sorting method
MOEA-NSGA-II
- 一个关于多目标优化的遗传算法参考程序,数值方法求解可行解-About multi-objective optimization genetic algorithm reference program
MOEA-NSGA-II
- NSGA算法是遗传算法在多目标优化上的实现，NSGA-2则是NSGA算法的改进算法，该程序包能实现NSGA-2的多目标优化-NSGA algorithm is a genetic algorithm on a multi-objective optimization, NSGA-2 is the improved algorithm NSGA algorithm, the package can achieve multi-objective optimization NSGA-2
MOEA-NSGA-II
- NSGAII(Non-Dominated Sorting in Genetic Algorithms) 进化算法，用于解决多目标问题的最经典算法，-a popular nondomination based genetic algorithm for multi-objective optimization
PICEAgMATLAB
- PICEA-g是一种有效智能多目标优化算法，算法性能，特别是在高维多目标优化问题上，优于传统的NSGA-II以及MOEA/D算法。并且算法无需额外的参数设置，简单易用。 -PICEA-g is a competitive multi/many-objective optimizer. Its performance is better or comparable to the state-of-the-art algorithms such as NSGA-II and MOEA/D on
MOEA-NSGA-II
- NSGA (No n- Do mina te d So r ting in Ge ne tic Alg o r ithms [5 ]) is a p o pula r no n-do mina tio n ba s e d g e ne tic a lg o r ithm fo r multi- o b je c tive o ptimiz a tio n. I t is a ve r y e ff e c tive a lg o r ithm but ha s b e e n g
MOEAs
- 多种多目标进化算法的集合，包括粒子群算法MOPSO，多目标遗传算法NSGA-II，以及MOEA/D等-a set of MOEAs,including MOPSO, NSGA-II, and MOEA/D.
MOEAFramework-master
- 多目标进化算法框架，包括MOEAD、NSGA2等经典多目标进化算法。-The MOEA Framework is a free and open source Java library for developing and experimenting with multiobjective evolutionary algorithms (MOEAs) and other general-purpose multiobjective optimization algorithms. Th
MOEA-NSGA-II
- MOEA-NSGA-II algorithm
NSGAII-and-MOEA-D-master
- NSGA2和MOEAD多目标进化算法，包含测试程序(NSGA2 and MOEAD multi-objective evolutionary algorithm, including test program)