搜索资源列表
up
- 运输问题的解,解决的双层规划的问题,up是上层文件
ActivdeSet
- 有效集法利用数学规划的对偶理论,将所求双层规划转化为一个下层只有一个无约束凸二次子规划的双层规划问题.然后根据两个双层规划的最优解和最优目标值之间的关系,提出一种简单有效的算法来解决非增值型凸二次双层规划问题.-Quadratic Bilevel Programming
GA-3
- 双层规划的遗传算法，用来解决非线性无约束双层规划- genic algorithm for bilevel programming
Solving
- 求解双层规划问题常用的算法有极点算法、直接搜索法、下降法和非数值优化方法(如模拟退火算法、遗传算法等)，遗传算法的求解思路是：首先对上层的决策变量编码，代人下层规划模型，通过求解下层模型的决策变量值，代入上层模型计算适应度值，然后进行交叉、变异、选择操作，最后求出最优解。-Solving Bilevel Programming Problems with pole algorithm commonly used algorithms, direct search method, descent
Level-programming-model-of-GA
- 双层规划模型的遗传算法求解的Matlab源码 GreenSim团队原创作品， -Level programming model of the genetic algorithm Matlab source GreenSim team original works,
Bi-level-programming-model-of-Matlab
- 双层规划模型的遗传算法求解的Matlab源码-Bi-level programming model of the genetic algorithm of Matlab source
GAU
- 基于matlab的双层规划遗传算法源代码，应用效果良好，请使用-Matlab the bilevel programming genetic algorithm source code, with good results, use
GA-for-Bilevel-Programming
- 双层规划模型的遗传算法求解的Matlab源码-GA for Bilevel Programming Model with Matlab
MYGA
- 双层规划的MATLAB代码，求解双层规划可以尝试采用-bi level programming
genetic-algorithm
- 双层规划模型的遗传算法求解的Matlab源码-Bi-level programming model of genetic algorithm
GA
- 求解双层规划的遗传算法,求解双层规划的遗传算法-Genetic Algorithm for Bilevel Programming
Bi-level-programming-model
- 双层规划模型，遗传算法，多目标优化，源代码-Bi-level programming model of basic Matlab source code
optimization-modelroad-network
- 双层规划，禁忌算法，道路交通规划，多目标优化-Based on the optimization model of regional road network double tabu genetic algorithm Pan Genan
bilevel-programming-model
- 基于双层规划模型的交通信号区域协调控制,城市道路交通规划小论文-Based on bi-level programming model of coordinated control of traffic signal area
newnew
- 遗传算法 用遗传算法求解双层规划模型得到最优解(genetic algorithm Solving Bilevel Programming Model with genetic algorithm to get the optimal solution)
双层规划-课件
- 算法介绍，双层规划模型，深层理解挖掘，适合规划初学者(algorithm and bi-level programming)
power system scheme
- 用遗传算法求解电网规划问题，双层算法求解，上层为遗传算法，下层利用拉格朗日对偶线性化后求解(Genetic algorithm is used to solve the power grid planning problem, double-layer algorithm is used to solve the problem, the upper layer is genetic algorithm, and the lower layer is solved by Lagrange dua