共查询到3条相似文献,搜索用时 15 毫秒
1.
Wu Li 《Mathematical Programming》1996,72(1):17-32
In this paper, we show that an analogue of the classical conjugate gradient method converges linearly when applied to solving
the problem of unconstrained minimization of a strictly convex quadratic spline. Since a strictly convex quadratic program
with simple bound constraints can be reformulated as unconstrained minimization of a strictly convex quadratic spline, the
conjugate gradient method is used to solve the unconstrained reformulation and find the solution of the original quadratic
program. In particular, if the solution of the original quadratic program is nondegenerate, then the conjugate gradient method
finds the solution in a finite number of iterations.
This author's research is partially supported by the NASA/Langley Research Center under grant NCC-1-68 Supplement-15. 相似文献
2.
We present a hybrid algorithm that combines a genetic algorithm with the Barzilai–Borwein gradient method. Under specific
assumptions the new method guarantees the convergence to a stationary point of a continuously differentiable function, from
any arbitrary initial point. Our preliminary numerical results indicate that the new methodology finds efficiently and frequently
the global minimum, in comparison with the globalized Barzilai–Borwein method and the genetic algorithm of the Toolbox of
Genetic Algorithms of MatLab.
相似文献
3.
增广Lagrange方法是求解非线性规划的一种有效方法.从一新的角度证明不等式约束非线性非光滑凸优化问题的增广Lagrange方法的收敛性.用常步长梯度法的收敛性定理证明基于增广Lagrange函数的对偶问题的常步长梯度方法的收敛性,由此得到增广Lagrange方法乘子迭代的全局收敛性. 相似文献