搜索资源列表
NSGA-II
- 演化、遗传计算方法NSGA2的源代码-evolution, genetic method NSGA2 the source code!
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
MOSGA2
- 基于ＮＳＧＡ-II方法的多目标遗传算法程序,本程序为通用包,可自行修改.-based NSGA-II method of multi-objective Genetic Algorithms procedures, the procedures for the general packet may amend its own.
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
nsga2code
- NSGA-II 多目标遗传算法 c语言编写
NSGA-II.rar
- 优化算法matlab代码
NSGAII optimization
- NSGA-II is a very famous multi-objective optimization algorithm. I submitted an example previously and wanted to make this submission useful to others by creating it as a function. Even though this function is very specific to benchmark problems, wit
NSGA-2
- NSGA-II is a very famous multi-objective optimization algorithm. I submitted an example previously and wanted to make this submission useful to others by creating it as a function. Even though this function is very specific to benchmark problems, wit
NSGA-II
- NSGA evaluate-objective
NSGA-II
- Multiobjective optimization codes using GA
NSGA-II
- NSGA是基于对个体的几层分级实现的。在选择执行 前,群体根据支配与非支配关系来排序:所有非支配个体被排成一类,这些被分级的个体共享它们的虚拟适应度值。然 后,忽略这组已分级的个体,对种群中的其它个体按照支配与非支配关系再进行分级,该过程继续直到群体中的所有个体被分级。(The NSGA is based on the individual layers of grading. Before selecting execution groups, according to govern with
NSGA-II
- 本程序是关于基于非支配排序遗传算法2的matlab程序，用于求解多目标优化问题的非支配解。(The non-dominated solutions of multi-objective optimization problems)
NSGA-II
- 多目标进化算法，带精英策略的非支配选择遗传算法(multi-objective evolution algorithm)
nsga
- NSGA2优化算法Matlab求解多目标优化问题,欢迎下载学习(NSGA2 optimization algorithm Matlab to solve multi-objective optimization problem, welcome to download and learn)
1985489NSGA-II
- 经典的多目标源代码，配有论文说明，供大家学习！(nsga_2 for multi-objective)
NSGA
- 轻松实现多目标优化，本文件自主设计，MATLAB平台实现(Easy implementation of multi-objective optimization, this document is designed independently.Implementation of MATLAB platform.)
NSGA2。5
- 多目标算法NSGA-2,亲测可用，求解方便，matlab编写，其中测试函数为ZDT1(Multiobjective algorithm NSGA-2, which can be used for pro-test and easy to solve, is compiled by matlab. The test function is ZDT1.)
NSGA
- 多目标遗传算法是NSGA-II[1]（改进的非支配排序算法）,该遗传算法相比于其它的多目标遗传算法有如下优点：传统的非支配排序算法的复杂度为 ，而NSGA-II的复杂度为 ，其中M为目标函数的个数，N为种群中的个体数。引进精英策略，保证某些优良的种群个体在进化过程中不会被丢弃，从而提高了优化结果的精度。采用拥挤度和拥挤度比较算子，不但克服了NSGA中需要人为指定共享参数的缺陷，而且将其作为种群中个体间的比较标准，使得准Pareto域中的个体能均匀地扩展到整个Pareto域，保证了种群的多样性
nsga代码
- nsga代码1. 利用nsga-i实现多目标opttmhzattonNSGA([5])是一种流行的基于非支配的多目标优化遗传算法。该算法是一种非常有效的算法，但由于其计算复杂度高、缺乏精英主义以及为共享参数oshare选择最优参数值而受到普遍批评。融合精英主义，不需要先验选择共享参数。本文将详细讨论NSGA-II。