搜索资源列表
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!
多目标优化 matlab
- multi object genetic algorithm 多目标优化遗传算法
spea2_matlab_code
- spea2多目标进化算法对两个目标的多目标优化问题的测试-spea2 multi-objective evolutionary algorithm on the two goals of testing multi-objective optimization problem
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 general, could be on this basis
multi-ctp1
- 一个基于阈值的粒子比较准则，用于处理多目标约束优化问题,该准则可以保留一部分序值较小且约束违反度在允许范围内的不可行解微粒,从而达到由不可行解向可行解进化的目的；一个新的拥挤度函数,使得位于稀疏区域和Pareto前沿边界附近的点有较大的拥挤度函数值,从而被选择上的概率也较大 从而构成解决多目标约束优化问题的混合粒子群算法。-A comparison based on the threshold criteria for the particle to handle multi-objective
ZW
- 约束优化进化算法，采用多目标优化算法的思想求解约束优化问题-constrained optimization evolutionary algorithms
deopt
- 使用matlab中仿真实现差分进化算法，可在多目标优化的应用的使用-matlab differential evolution (DE) algorith
excise_lanjiabiao_NSGA_2
- 多目标优化 进化算法 优化问题 实现两个目标变量的NSGA2的优化程序-Multi objective optimization Evolutionary algorithm
MOEAD
- 多目标优化算法moea/d算法代码的源代码，遗传算法，进化算法。-Multiobjective Evolutionary Algorithm Based on Decomposition
NSGA-II
- 一种快速多目标遗传算法，NSGA-Ⅱ是目前最流行的多目标进化算法之一，它降低了非劣排序遗传算法的复杂性，具有运行速度快，解集的收敛性好的优点，成为其他多目标优化算法性能的基准。-A fast multi-objective genetic algorithm, NSGA-Ⅱ is the most popular one multi-objective evolutionary algorithm, which reduces the non-dominated sorting genetic
SPEA2_MATLAB
- SPEA2用于解决多目标优化算法的多目标进化算法，作为经典算法，常常被用来对比-Many engineering problems are characterized by several, often contradicting objectives, that have to be satisfied simultaneously.Strengthen Pareto Evolutionary Algorithm 2 (SPEA 2) is a Multi-Objective Evolutio
粒子群算法
- 微粒群算法 目标粒子群优化算法的matlab版本。最经典的多目标进化算法！
MOPSO
- 多目标粒子群优化，是一种基于种群的进化算法，每次迭代能产生出一组非劣解，经过适当的扩展可适于求解多目标优化问题。-Multi-objective particle swarm optimization, evolutionary algorithm is a population-based, each iteration produces a set of non-dominated solutions, through appropriate extension may be adapted
ypea124-moea-d
- 基于分解的多目标进化算法，将多目标函数分解成多个单目标优化问题进行求解各工程问题。-Multi-objective evolutionary algorithm based on decomposition, the multi-objective function is decomposed into a plurality of single-objective optimization problem to solve various engineering problems.
NSGA-ii
- 多目标,NSGA-II,本代码的作用是用进化算法进行多目标优化，编辑语言是MATLAB-Mutilobjective optimization
spMODE
- 该代码基于偏好实现了具有球形修剪的多目标差分进化算法的版本，有改进和处理的机制：多样性，针对性，多目标优化实例以及受限优化实例。(It is a MOEA with mechanisms to improve and deal with:Diversity, Pertinency, Many-objective optimization instances, Constrained optimization instances.)
多目标优化的微分进化算法
- 差分算法，求最优解，能实现，能运行，是个测试版本，可以在这基础改(Genetic algorithm, the best solution, can be realized, can run, is a test version, can be modified in this basis.)
MOEA-D-DE
- 基于分解的多目标进化优化算法，在2007年提出的，是另外一种求解多目标优化问题流行的算法。常用(The decomposition-based multi-objective evolutionary optimization algorithm, proposed in 2007, is another popular algorithm for solving multi-objective optimization problems.The commonly used)
MOEAD_
- 多目标优化算法，首先运用切比雪夫算法分解，然后通过进化算法求解(The multi-objective optimization algorithm,which first solved by Chebyshev algorithm and then solved by evolutionary algorithm.)
多目标进化+多目标粒子群优化代码
- 多目标粒子群优化，多目标进化算法，两种方法能够有效的解决复杂的优化问题(optimization based on intelligent swarm)