Description: 用基于拉格朗日函数Hesse阵的SQP方法求解约束优化问题-Hesse matrix based on Lagrange function with the SQP method for solving constrained optimization problems Platform: |
Size: 2048 |
Author:蔡萃英 |
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Description: matlab程序非线性优化设计方法时下流行的关于非线性规划的源程序,包括SQP方法、乘子法程序、二次规划、非线性最小二乘法、共轭梯度法、拟牛顿法、线搜索技术、信赖域方法、最速下降法与牛顿法等-matlab program nonlinear optimization design method popular on nonlinear programming source code, including the SQP method, the multiplier method procedures, quadratic programming, nonlinear least squares method, the conjugate gradient method, quasi-Newton method, the linesearch technology, trust region methods, the steepest descent method and Newton method Platform: |
Size: 34816 |
Author:朱志远 |
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Description: 控制问题转化为了数学规划问题。推导出目标函数对于待求参数的梯度公式,并利用序列二次规划算法求出最优控制量-the problem is changed into mathematical programming problem and formulae are derived for computing the gradients, also, a computational method for finding the optimal control is obtained by using the Sequential Quadratic Programming (SQP) algorithm. Platform: |
Size: 33792 |
Author:geege |
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Description: SQP方法是求解约束优化问题最有效的算法之一-SQP method is one of the most effective algorithm for solving constrained optimization problems
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Size: 12288 |
Author:路多多 |
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Description: SQP method is one of the most effective algorithm for solving constrained optimization problems
Platform: |
Size: 686080 |
Author:路多多 |
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Description: 序列二次算法求大量的约束优化问题,外文,非常好的文献-Sequential Quadratic algorithm for a large number of constrained optimization problems, foreign languages, very good literature Platform: |
Size: 265216 |
Author:wenxiaoqiang |
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Description: Differential Evolution with Self-adaptation and Local Search for
Constrained Multiobjective Optimization Platform: |
Size: 1761280 |
Author:Iman |
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Description: 序列二次规划(SQP)方法被认为是解决非线性约束优化最有效的方法之一,传统的SQP算法每一步迭代都要求解QP子问题。
(Sequential two times programming (SQP) is considered to be one of the most effective ways to solve nonlinear constrained optimization. The traditional SQP algorithm requires QP iteration for every iteration.) Platform: |
Size: 12288 |
Author:labuladuo
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