搜索资源列表
nsga-2
- 快速非支配排序算法，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。(The fast non dominated sorting algorithm introduces the elite strategy to ensure that some excellent individual individuals will not be discarded during
Multi-objective-evolutionary
- NSGA的源程序，是多目标进化算法的智能算法，可用于多目标优化与决策等方面的计算(NSGA source, multi-objective evolutionary algorithm intelligent algorithm can be used to calculate other multi-objective optimization and decision-making)
带约束的遗传优化算法
- 带约束的多目标遗传优化算法NSGA-II(Constrained Multi-objective Genetic Algorithms NSGA-II)
nsga
- 实例分析，运用MATLAB中自带的多目标遗传算法对多目标函数进行计算，找到帕累托最优解。(Case study shows that the multi-objective genetic algorithm in MATLAB is used to calculate the multi-objective function and find the Pareto optimal solution.)
NSGA-III
- 一种改进的适用于高维的进化算法，采用参考点等方法。(evolutionary algorithm)
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
NSGAII-有约束限制的优化问题
- 基于NSGA-II的有约束限制的优化问题实例matlab编程代码(Matlab programming code based on nsga-ii constrained optimization problem)
NSGA2_IGD&GD
- nsga2算法，测试指标IGD和GD，测试函数ZDT1-ZDT4,DTLZ1-DTLZ4(NSGA2 algorithm, index metrics IGD and GD, test functions ZDT1-ZDT4, DTLZ1-DTLZ4)
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)
NSGA-II-Matlab-master
- 针对带有约束条件的多目标函数，进行多目标参数优化(For the multi-objective function with constraints, the optimization is carried out)
NSGA2 正确
- 运用NSGAⅡ求解多目标柔性作业车间调度，其中目标主要包括时间和能耗(NSGA2 is used to solve multi-objective flexible job shop scheduling,in which the objectives mainly include time and energy consumption)
NSGA-II多目标优化算法matlab程序
- 遗传算法程序NSGA2，关于移动机器人路径规划。(Matlab program of path planning based on NSGA2 genetic algorithm)
0cb728ca
- 使用NSGA2求解作业车间调度问题，可以运行，亲测有效(Using NSGA2 to solve job shop scheduling problem)