搜索资源列表
NSGA2 ——FSP
- 遗传算法2 求解柔性作业车间 调度问题 matlab 编码(use NSGA II to solve the flexible job shop scheduling problem)
duxpd
- nsga2_c多目标优化算法：NSGA-II算法()
multi-objective power flow optimization
- 构建了含VSC-HVDC的交直流系统多目标最优潮流模型；针对此模型连续变量和离散变量共存的特点，提出了内点法和NSGA2算法相结合的交替求解算法，可获得多个Pareto最优解，并具有较高的计算效率(Considering the coexistence of continuous and discrete variables in this model,an alternative solution method based on the interior point method and NS
MA-NSGA-II-原始
- 基于多目标遗传算法的 两点路径规划求解方法。(route searching method based on Multi- objective optimization algorithm)
煤矿节能减排多目标优化研究
- 针对传统煤矿节能减排优化模型选取的目标函数比较单一的问题,构建了涵盖经济效益、能源消耗、污染物排放量等目标函数的煤矿节能减排多目标优化模型,并应用基于改进的蝙蝠算法寻找3个目标函数之间的优化解,实现了经济效益最大化、能源消耗最低化、污染物排放量最少化的优化结果。仿真结果表明,相比于PSO-E、NSGA-II算法,改进的蝙蝠算法能够在较短的迭代步数内获取较高的个体适应度,且能够实现较佳的多目标优化结果,符合节能规划的目标需求。(Aiming at the problem that the obje
SeismoSignal_v5.0.0
- 11更健康更可能 案例看过来个按个垃圾管理奥利给来几个拉个垃圾垃圾理工老牛拉几个纳格兰丽娜率经历过阿拉基过来拿了(dhgfdagjlagagljaomg am ajgm aljg lamg. anljamganlajlm agnlagnhoegnl g a)
evaluate_objective
- 利用NSGA-II算法实现水资源配置多目标优化问题——目标函数；(Realization of multi-objective optimization of water resources allocation based on NSGA-II algorithm_objectives;)
genetic_operator
- 利用NSGA-II算法实现水资源配置多目标优化问题——基因操作；(Realization of multi-objective optimization of water resources allocation based on NSGA-II algorithm_genetic operator)
initialize_variables
- 利用NSGA-II算法实现水资源配置多目标优化问题——初始变量；(Realization of multi-objective optimization of water resources allocation based on NSGA-II algorithm_initialize variables)
nsga_2
- 利用NSGA-II算法实现水资源配置多目标优化问题——nsga2算法(Realization of multi-objective optimization of water resources allocation based on NSGA-II algorithm_nsga2)
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 the evolution process, thus i
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 realize multi-objective optimiza
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)